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Respiratory muscle oxygenation and myoelectrical manifestations during normoxic and hypoxic inspiratory… Basoudan, Nada 2015

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 RESPIRATORY MUSCLE OXYGENATION AND MYOELECTRICAL MANIFESTATIONS DURING NORMOXIC AND HYPOXIC INSPIRATORY THRESHOLD LOADING  by Nada Basoudan BSc.PT, King Saud University, 2008  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE  in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Rehabilitation Sciences)    THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)  January 2016     © Nada Basoudan, 2015    ii  Abstract Objectives: To examine the acute effect of hypoxia and inspiratory threshold loading (ITL) on (1) oxygenation of inspiratory muscles (sternocleidomastoid [SCM], scalene [SA] and parasternal [PS]) and, (2) electromyography (EMG) of the SA and SCM in healthy adults using near-infrared spectroscopy (NIRS) and linear array EMG respectively. Methods: Twenty healthy adults (12M/8F) were randomly assigned to perform two ITL tests while breathing a normoxic (Norm) or hypoxic (HYP, FIO2=15%) gas mixture. NIRS devices were placed over the SCM, PS, SA, and a control muscle, tibialis anterior (TA), to monitor oxygenated (O2Hb), deoxygenated (HHb), and total hemoglobin (tHb) as well as tissue saturation index (TSI). SA and SCM activation were evaluated based on a normalized EMG amplitude, whereas fatigue was expressed as a decline in EMG median frequency during maximal inspiratory pressure maneuvers after ITL. Subjects breathed the randomly-assigned gas mixture through the ITL device where the load was increased every two minutes until task failure. Maximal inspiratory pressure (MIP) and dyspnea were recorded before and after ITL. Also, arterial oxygen saturation (SpO2),  electrocardiogram (EKG) and ventilatory measures were monitored throughout the test. Result: Subjects were aged 31+12 years. At task failure, the maximum load, ventilatory parameters and dyspnea perception did not differ between the two ITL tests. At HYP-ITL task failure, SpO2 was significantly lower, and HHb increased more extensively in SA, SCM and PS than Norm-ITL. SCM TSI decreased more during HYP-ITL compared with Norm-ITL. tHb in the inspiratory muscles increased significantly compared to the decrease in TA during both tests. A subgroup analysis of 13 subjects (9M/4F) revealed that SA and iii  SCM were progressively recruited during Norm-ITL and to a higher extent during HYP-ITL. However, EMG median frequency and MIP did not decline after both ITL tests. Conclusion: The SCM was the most vulnerable to deoxygenation during incremental loading. The increase in SA and SCM EMG is reflective of increased ventilatory loads. Taken together, the deoxygenation and the activation of inspiratory muscles were accentuated by acute hypoxia. These findings suggest that task failure occurred because of other factors such as hypoventilation and dyspnea rather than peripheral muscle fatigue.             iv  Preface This dissertation contains the work of a research study conducted by Nada Basoudan under the supervision of Dr. W. Darlene Reid. The Neural Control of Force Production and Movement Lab have lent us the EMG amplifier. Also, Alessio Gallina assisted with EMG data analysis. The study design, data collection data analysis, and writing the manuscript were primarily the work of the candidate. A selection of work from this thesis will be submitted for publication in peer-reviewed journals. Ethical approval was obtained from the Vancouver Coastal Health Research Institute (V14-00952) and the University of British Columbia‘s Clinical Research Ethics Board (H14-00952). Published abstract: Basoudan, N., Shadgan, B., Guenette, J.A., Road, J., & Reid, W.D. (2015, September). The effect of normobaric hypoxia on respiratory muscle oxygenation during incremental inspiratory threshold loading (ITL) in healthy adults. Poster session presented at the European Respiratory Society International Congress, Amsterdam, NL. Contribution:  Nada Basoudan was responsible for the construction of the poster. Babak Shadgan, Jordan A. Guenette, Jeremy Road and W. Darlene Reid each of whom thoughtfully edited and reviewed the abstract. v  Submitted paper: A version of Chapter Two is submitted for publication in a peer-review journal. Nada Basoudan, Babak Shadgan, Jordan A. Guenette, Jeremy Road, W. Darlene Reid. Effect of acute hypoxia on inspiratory muscle oxygenation during incremental inspiratory loading in healthy adults. [under review] Contribution:  Nada Basoudan was responsible for data collection, analysis and the majority of manuscript preparation. W. Darlene Reid, the supervisory author, was involved throughout the project from designing the study to editing the manuscript. Babak Shadgan and Jeremy Road were involved in the early stage of concept formation and contributed to manuscript edits. Jordan A. Guenette assisted with setting the ventilatory acquisition system as well as provided valuable feedback on the manuscript.  To be submitted: A version of Chapter Three will be submitted for publication in a peer-review journal. Nada Basoudan, Alessio Gallina, S. Jayne Garland, Jordan A. Guenette, Babak Shadgan, Jeremy Road, W. Darlene Reid. Inspiratory muscle myoelectric manifestations and task failure during normoxic and hypoxic inspiratory loading Contribution:  Nada Basoudan was responsible for data collection, analysis and the majority of manuscript preparation. W. Darlene Reid, the supervisory author, was involved throughout vi  the project from designing the study to editing the manuscript. Babak Shadgan, Jeremy Road and S. Jayne Garland were involved in the early stage of concept formation and contributed to manuscript edits. Jordan A. Guenette assisted with setting the ventilatory acquisition system as well as provided valuable feedback on the manuscript. Alessio Gallina assisted with data collection, programming for analysis and manuscript composition.             vii  Table of Contents Abstract ................................................................................................................. ii Preface .................................................................................................................. iv Table of Contents ................................................................................................ vii List of Tables ........................................................................................................ xi List of Figures ...................................................................................................... xii List of Abbreviations .......................................................................................... xiv Acknowledgments ............................................................................................. xviii Dedication ............................................................................................................ xix Chapter One: Introduction .................................................................................. 1 1.1 Introduction ................................................................................................. 1 1.1.1 Respiratory system and oxygen transport to tissue .......................... 1 1.1.2 Respiratory muscle function................................................................ 2 1.1.3 Inspiratory muscle strength and endurance assessment .................. 5 1.1.4 Near-infrared spectroscopy (NIRS) .................................................... 6 Types of near-infrared spectroscopy ........................................... 7 Continuous wave near-infrared spectroscopy principle ..... 7 viii Near-infrared spectroscopy measurement validity .................... 8 Near-infrared spectroscopy applications for muscles ................ 9 Respiratory muscle oxygenation and hemodynamics ........ 12 1.1.5 Electromyography .............................................................................. 15 Type of electromyographic electrodes ....................................... 16 1.1.6 Gas exchange during exercise ........................................................... 22 1.1.7 Causes of arterial hypoxemia ............................................................ 23 1.1.8 Types of hypoxia ................................................................................. 24 Acute cardio-respiratory response to hypoxia at rest .............. 25 Acute cardio-respiratory response to hypoxia during exercise26 Muscular response to hypoxia .................................................... 28 Hypoxic effects on respiratory muscle ................................ 29 1.1.9 Overall study rationale ...................................................................... 32 1.2 Objectives and hypotheses of the thesis .................................................. 34 Chapter Two: Effect of acute hypoxia on inspiratory muscle oxygenation during incremental threshold loading in healthy adults ............................................. 36 2.1 Introduction ............................................................................................... 36 2.2 Methods ...................................................................................................... 38 2.2.1 Experimental protocol ....................................................................... 39 ix  2.2.2 Near-infrared spectroscopy ............................................................... 40 2.2.3 Inspiratory threshold loading (ITL) ................................................. 42 2.2.4 Statistical analysis............................................................................... 44 2.3 Results ........................................................................................................ 45 2.4 Discussion ................................................................................................... 49 2.4.1 Study limitations ................................................................................. 55 2.4.2 Conclusions ......................................................................................... 55 Chapter Three: Inspiratory muscle myoelectric manifestations and task failure during normoxic and hypoxic inspiratory loading: A Pilot study ................. 57 3.1 Introduction ............................................................................................... 57 3.2 Methods ...................................................................................................... 59 3.2.1 Participants ......................................................................................... 59 3.2.2 Experimental procedure .................................................................... 60 3.2.3 Spirometry .......................................................................................... 62 3.2.4 Inspiratory threshold loading protocol ............................................ 62 3.2.5 Respiratory muscle activity (EMG) .................................................. 63 3.2.6 Ventilatory parameters ...................................................................... 64 3.2.7 EMG data processing ......................................................................... 66 3.2.8 Statistical analysis............................................................................... 67 x  3.3. Results ....................................................................................................... 68 3.3.1 Descriptive characteristics ................................................................. 68 3.3.2 Ventilatory parameters ...................................................................... 68 3.3.3 SpO2, HR, MAP and dyspnea............................................................ 70 3.3.4 EMG .................................................................................................... 71 3.4 Discussion ................................................................................................... 72 3.4.1 Study limitations ................................................................................. 76 3.4.2 Conclusions ......................................................................................... 77 Chapter Four: ..................................................................................................... 78 4.1 Summary .................................................................................................... 78 4.2 Future directions ....................................................................................... 84 References ............................................................................................................ 86 Appendix A: Consent form .............................................................................. 128 Appendix B: The American Heart Association and American College of Sport Medicine Health/ Fitness Facility Pre-participation Screening Questionnaire. ..... 135 Appendix C: Modified Borg Dyspnea Scale. .................................................. 136 Appendix D:Examination sheet ....................................................................... 137 Appendix E: Vital signs and dyspnea recording sheet .................................. 138 xi  List of Tables Table 2.1 Anthropometric and spirometric data…………………………………….…. 45    Table 2.2 Effects of normoxic and hypoxic ITL on performance, ventilatory  and cardiac parameters at rest and task failure…………………….…..…………..….  46 Table 3.1 Anthropometric and spirometric data……………………………….……… 68 Table 3.2 Ventilatory parameters at baseline, 20, 40, 60, 80% and task  failure of Norm-ITL and HYP-ITL ……………………………………………..……. 69           xii  List of Figures  Figure 1.1 A schematic view of a NIRS probe penetrating a biological tissue ……..….  8 Figure 1.2 Schematic presentation of acquired EMG signals by linear array electrode….19  Figure 2.1 Inspiratory threshold loading device ……………….………………...……... 42 Figure 2.2 Change in NIRS variables of the four muscles from baseline to task        failure …………………………………………………………………………………... 47  Figure 2.3 Change in HHb of all four muscles and  in TSI for SCM, PS and TA                       during each quintile of ITL ………………………………….………………………… 48 Figure 3.1 Schematic representation of the experimental design of the study ……….. 60 Figure 3.2 An outline of  ITL protocol  …………………………..…………..………  61 Figure 3.3 ITL set-up; A: Breathing apparatus, B: Data acquisition,  C: Non-diffusing gas reservoir bag  ……………………………….………………………………….…  63 Figure 3.4 Ventilatory parameters from a representative subject ………….…….…...  65 Figure 3.5 A: Raw EMG data from SA and SCM, B: selected channels and time window. Blue signals indicate the last five breaths of  the each interval……….....….  67 Figure 3.6 Arterial oxygen saturation via pulse oximetry (SpO2), heart rate (HR),                             and  mean arterial pressure (MAP) ………………………………………………….   70 xiii  Figure 3.7 Maximum inspiratory pressure (MIP) and associated EMG median frequency of SA and SCM during MIP maneuver  ………………………………………..….…..  71     Figure 3.8 RMS of SA and SCM at 20, 40, 60, 80% and task failure of ITL. Black bars indicate Norm-ITL, whereas the gray bars indicate HYP-ITL ................................…...  72              xiv  List of Abbreviations c: The concentration of the chromophore CHF: Chronic heart failure  cm: Centimeter cmH2O: Centimeter of water COPD: Chronic obstructive pulmonary disease  CO2: Carbon dioxide DPF: Differential pathlength factors  ɛλ: The extinction coefficient of the chromophore EKG: Electrocardiogram EIAH: Exercise-induced arterial hypoxemia  EMG: Electromyography  fB: Breathing frequency FVC: Forced vital capacity FVC: Predicted normal value of forced vital capacity FEV1: Forced expiratory volume in 1 second  FEV1/FVC: The ratio of the forced expiratory volume in the first one second to xv  the forced vital capacity of the lungs FEV1  pred: Predicted normal value of forced expiratory volume in 1 second  FEV1/FVC pred: Predicted normal value of the ratio of the forced expiratory volume in the first one second to the forced vital capacity FIO2: Fractional concentration of inspired oxygen  FVC: Forced vital capacity HHb: Deoxygenated hemoglobin  HR: Heart rate  ICG: Indocyanine green dye  ITL: Inspiratory threshold loading  L: The distance between light entry and exit point,   l: liter m: Meter MAP: Mean arterial pressure MIP: Maximum mouth inspiratory pressure MIP pred: Predicted normal value of  maximum mouth inspiratory pressure Min: Minute xvi  mm: Millimeter mmHg: Millimeter of mercury  ms: Milliseconds  nm: Nanometer NIRS: Near-infrared spectroscopy  OD R,λ: Reflects the independent oxygen light lost due to scattering in the tissue. ODλ: The optical density of the medium, O2Hb: Oxygenated hemoglobin  PaCO2: Arterial partial pressure of CO2  PaO2: Arterial partial pressure of O2  PAO2: Alveolar partial pressure of oxygen  PETCO2: End-tidal carbon dioxide partial pressure PETO2: End-tidal O2 pressure  PmPeak : Peak mouth pressure Pm: Mouth pressure PS: Parasternal RMS: Root mean square  xvii  SA: Scalene sEMG: Surface electromyography  SCM: Sternocleidomastoid SpO2: Saturation of hemoglobin with oxygen as measured by pulse oximetry TA: Tibialis anterior tHb: Total hemoglobin concentration  TSI: Tissue saturation index  VA/Q: Ventilation-perfusion ratio  VCO2: Carbon dioxide production  VE: Minute ventilation  VO2: Oxygen consumption VO2 max: Maximal oxygen consumption  VT: Tidal volume  WRmax: Maximal work rate  %:  Percentage  µm: Micromolexviii  Acknowledgments This research would not have been possible without the support of a number of individuals. I would like to express my deepest appreciation to my supervisor Dr. W. Darlene Reid for her mentorship and encouragement throughout this journey. I have become more meticulous and more motivated to dedicate my future career. I have learned how to overcome challenges while making meaningful progress. I would also like to express my gratitude to my committee members Drs. S. Jane Garland, Babak Shadgan and Jeremy Road for their invaluable guidance and support. Lastly, I would like to thank  Dr. Bill Sheel for acting as external examiner for my thesis defense. I am incredibly grateful to Dr. Jordan Guenette, who has given me invaluable assistance in setting up the ventilatory data acquisition and for Alessio Gallina, who has helped me on EMG data analysis. In addition, I would like to extend a heartfelt thanks to my husband and all of my family for their support, love, words of wisdom and patience. I could not have done it without you. I greatly appreciate all my lab members (Emily, Alka and Carmen) for all the advice and assistance. Lastly, I would like to thank the funding resource (Princess Nora Bint Abdul Rahman)    xix  Dedication To all my family “ Husband, Mother, Father, Brothers, Sisters, Grandmothers, Grandfathers, Uncles, Aunts, Nephews, and Nieces.”           1  Chapter One: Introduction 1.1 Introduction 1.1.1 Respiratory system and oxygen transport to tissue Supplying the blood with sufficient oxygen is a crucial role played by the lungs. To sustain normal metabolic cellular function, cells require a constant oxygen supply from the cardio-respiratory system. During inspiration, oxygen is transported from inhaled air from the atmosphere to the alveoli, where oxygen diffuses across the cell membrane into the bloodstream and binds to hemoglobin in red blood cells. With each heartbeat, oxygenated blood is pumped to all of the body’s cells where oxygen detaches from hemoglobin and diffuses into the mitochondria. Generating adequate thoracic pressure during inspiration is accomplished by the coordinated activity of the primary and the accessory respiratory muscles (De Troyer & Estenne, 1984). Indeed, several factors likely contribute to respiratory muscle function such as age (Chen & Kuo, 1989), sex (Romei et al., 2010), breathing pattern (Breslin, 1992), body mass index (Evans &Whitelaw, 2009; Nava, Ambrosino, Crotti, Fracchia, & Rampulla, 1993), body position (Hodges, Gandevia, & Richardson 1997; Saunders et al., 2004) and the presence of cardio-respiratory (Hopkinson, Dayer, Moxham, & Polkey, 2010; O’Neill & McCarthy, 1983) or neuromuscular disease (Gosselink, Kovacs, & Decramer, 1999; Haas, Trew, & Castle, 2004; Mellies & Lofaso, 2009).  A change in ventilation pattern and respiratory muscle recruitment requires a shift in respiratory neural drive (Jolley et al., 2009). Respiratory muscle activation is controlled by two descending pathways: involuntary activation is controlled by the bulbospinal pathways 2  in the medulla, whereas voluntary activation is controlled by corticospinal pathways (Mitchell & Berger, 1975). Moreover, ventilatory responses to the change in the arterial partial pressure of oxygen (PaO2) and the arterial partial pressure of carbon dioxide (PaCO2) levels are regulated via the central and the peripheral chemoreflex. Central chemoreceptors respond to hypercapnic stimulation and are located on the ventral surface of the medulla (Guyenet et al., 2010), whereas peripheral chemoreceptors are sensitive to hypoxia and are found in the carotid and aortic bodies (Nurse, 2010). Most studies that examined the central chemoreflex used the hypercapnic rebreathing technique, whereas the hypoxic rebreathing technique was utilized to evaluate the peripheral chemoreflex (Ainslie & Burgess, 2008;  Cooper, Pearson, Bowker, Elliott, & Hainsworth, 2005; Van Klaveren & Demedts, 1998).  1.1.2 Respiratory muscle function Respiratory muscles are classified according to their function and recruitment during the ventilatory cycle. In healthy humans, during quiet breathing, the inspiratory muscles are activated during the inspiratory phase of the ventilatory cycle, whereas expiration is passive (De Troyer, Ninane, Gilmartin, Lemerre, & Estenne, 1987). Moreover, during inspiration, the contraction of the inspiratory muscles creates a negative pressure in the thoracic cavity, drawing air into the lungs. On the other hand, during expiration, the release of muscle tension and upward movement of the diaphragm reduces the thoracic pressure (Butler, 2007). However, to optimize ventilatory efficacy during high ventilatory loads that could be experienced during exertion or respiratory compromise, both expiratory and accessory muscles are activated. It is well known that the diaphragm, rather than other inspiratory muscles, is highly resistant to fatigue because it has a unique composition of muscle fibers and multiple blood supply sources (Stubbings et al., 2008). Moreover, given 3  its role as a primary inspiratory muscle, approximately 60-80% of total inspiratory work is performed by the diaphragm, whereas the SCM contribution is about 10% of the total inspiratory work during high ventilatory efforts (Ratnovsky & Elad, 2005).  When healthy subjects exercise, respiratory muscle function becomes complex, in which a shift in the recruitment pattern of the inspiratory muscle appears at the maximal ventilatory efforts (Chiti et al., 2008; Jonville, Jutand, Similowski, Denjean, & Delpech, 2005). It is even more complicated in patients with respiratory or neuromuscular diseases (Barreiro & Gea, 2015;  Haas et al., 2004; Klimathianaki, Vaporidi, & Georgopoulos, 2011). In patients with chronic obstructive pulmonary disease (COPD), for instance, the inspiratory muscles face increased loads as a result of increased inspiratory airflow resistance, minute ventilation and breathing frequency. Concomitantly, increased end-expiratory lung volume and chest hyperinflation attenuate the mechanical advantage of the diaphragm and other inspiratory muscles (Laghi & Tobin, 2003). Respiratory muscle dysfunction is one of the foremost clinical manifestations of acute and chronic respiratory failure in patients with COPD (Budweiser, Jörres, & Pfeifer, 2008; Calverley, 2003). Furthermore, respiratory muscle dysfunction has been correlated with hospitalization and mortality in patients with COPD (Vilaró et al., 2010; Zielinski, 1997).  In the clinical setting, evaluating the inspiratory muscles is important, since they can signal increased ventilatory workloads and reflect pending respiratory distress. Early detection of signs of imminent failure may lead to more effective treatment and recovery of dysfunctional respiratory muscles. Respiratory failure due to respiratory muscle dysfunction can be acute or chronic in its onset.  Regardless of its progression, a non-invasive tool that shows early signs of ventilatory failure would be very useful in 4  monitoring people with chronic conditions, acute conditions and during weaning from mechanical ventilation. Therefore, monitoring respiratory muscle function is highly important to ensure adequate ventilation when ventilatory demand increases. Several techniques are used to assess respiratory muscle function. Respiratory muscle strength is frequently used as a basic measurement. In some cases, extensive examination is required. Thus, electromyography (EMG) could be used to assess muscle recruitment and fatigue. Although near-infrared spectroscopy (NIRS) is not yet considered as a standard measure of respiratory muscle function, it provides valuable insight into respiratory muscle oxygenation.  Quantifying regional tissue oxygenation remains a challenge in a routine clinical setting. Indeed,  critically ill patients are at high risk for tissue hypoxia that may occur because of systematic hypoxemia, impaired diffusion or anemia (Huang, 2005). However, systemic arterial and venous oxygenation are evaluated routinely with widely proved methods like pulse oximetry and blood gas analysis. Pulse oximetry is the most popular, simplest and most inexpensive device that determines the oxygen saturation in the arterial blood (SpO2) through the finger, toe, nose or earlobe during each cardiac cycle by measuring the light attenuation. However, the accuracy of the measurement is questionable for detecting SpO2 for critically ill subjects. For instance, SpO2 is underestimated in cases of hypotension, hypothermia and anemia, whereas it is overestimated when SpO2 falls below 75% (Crouser & St. John, 1995). Pulse oximetry does not reflect the sufficiency of CO2 elimination. Therefore, it reflects systemic hypoxemia, not hypercapnia (ED. Chan, Chan, & Chan, 2013). Furthermore, regional ischemia is not detectable by pulse oximetry. Thereby, the 5  NIRS method reveals the oximetry gap by permitting early detection of regional tissue hypoxia, which is essential in critical care management. 1.1.3 Inspiratory muscle strength and endurance assessment Inspiratory muscle strength and endurance can be assessed using several approaches. Strength can be estimated by measuring the inspiratory pressure that develops during either voluntary (i.e. maximal mouth inspiratory pressure (MIP), nasal sniff pressure)  or involuntary maneuvers (i.e. phrenic nerve stimulation) (Steier et al., 2007). Inspiratory muscle endurance is gauged as the duration for which an inspiratory load can be sustained or the maximal inspiratory loads can be tolerated (Gibson et al., 2002). Endurance can be assessed by a number of tests including inspiratory threshold loading (ITL) and resistive loading, where subjects have to sustain sufficient inspiratory pressure in order to acquire airflow. The progression of endurance tests intensity could be constant when a subject breathes against a finite external load, or incremental when the load is progressively increased every two to three minutes until task failure.  The ITL protocol has been used for training the respiratory muscles in COPD patients (Charususin et al., 2013; O’Brien, Geddes, Reid, Brooks, & Crowe 2008), healthy subjects (Chatham, Baldwin, Griffiths, Summers, & Enright, 1999) and athletes (Kilding, Brown, & McConnell, 2010). Moreover, good reproducibility of incremental ITL has been confirmed in naïve healthy subjects (P.H Johnson, Cowley, & Kinnear, 1997).  A variety of loading devices are available; one of the fundamental devices is the weighted plunger that was first designed by Nickerson and Keens (1982). The weighted plunger is utilized as a testing instrument to assess inspiratory muscle endurance as well as being employed 6  as a training device. McElvaney, Fairbarn, Wilcox, & Pardy (1989) proved the reproducibility of using the weighted plunger to impose incremental ITL to test inspiratory muscle performance over time. Another device, the spring-loaded valve/threshold inspiratory trainer, was invented in 1988 and shares a similar loading principle with the weighted plunger (Larson, Kim, Sharp, & Larson, 1988). Of note, there was no significant difference between using the weighted plunger or the spring-loaded valve in training effectiveness (P.H. Johnson, Cowley, & Kinnear, 1996). In fact, the portability and simplicity of the spring-loaded valve device favor its application in cases of home-based training programs.  1.1.4 Near-infrared spectroscopy (NIRS) The development of NIRS provides an opportunity to compare the pattern of changes in tissue oxygenation and blood flow at the level of small blood vessels, arterioles and capillaries in skeletal muscle (Hamaoka et al., 2007), cerebral tissue (Miyazawa et al., 2013) and other organs (Schulz et al., 2002; Stothers, Shadgan, & Macnab, 2008). The concept of measuring tissue oxygenation in vivo with light was established by Milikan (1937) who studied soleus muscle oxygenation in cats. A number of investigators worked to improve the optical technology to study muscle oxygenation in animals (Chance & Jobsis, 1959; Chance & Weber, 1963). However, the actual inception of NIRS occurred in 1977, when the change in tissue oxygenation of the heart and brain of laboratory animals was non-invasively monitored via NIRS (Jöbsis, 1977). In 1988, Hampson and Piantadosi conducted the first study that measured the oxygenated hemoglobin (O2Hb) in human skeletal muscle using NIRS. Since then, the utilization of NIRS has increased considerably. 7 Types of near-infrared spectroscopy There are three fundamental types of NIRS instrumentation: continuous wave, frequency domain and time-resolved (Pellicer & Bravo, 2011). The continuous wave NIRS is the most common instrument used in human and animal studies. Over the last decade, continuous wave NIRS technology has seen rapid expansion in the development of instrumentation, which has resulted in an extensive number of inventions. With the rapid evolution of NIRS technology, the spatially resolved NIRS devices are designed to measure tissue saturation index (TSI), which is an absolute measure of tissue oxygenation. Continuous wave near-infrared spectroscopy principle The principle of continuous wave NIRS is based on measuring the difference in the optical density of near-infrared light that is emitted from the transmitters and detected by a receiver (Figure 1.1). NIRS travels through biological tissue in a scattered arch pattern and is absorbed by blood chromophores. The wavelengths of the infrared spectrum range between 700 and 1,000 nm. Each wavelength is absorbed by a specific blood chromophore. Primarily, deoxygenated hemoglobin (HHb) and O2Hb concentration, the two major NIRS measures, are sensitive to 760 and 850 nm wavelengths, respectively.  It is of importance to emphasize that both hemoglobin and myoglobin are represented in the near-infrared spectrum (Mancini et al., 1994). However, myoglobin absorbs minimal light compared with hemoglobin (Belardinelli, Barstow, Porszasz, & Wasserman, 1995; Mancini et al., 1994; Wilson et al., 1989). The concentration of HHb and O2Hb can be obtained by the modified Beer-Lambert Law (Delpy et al., 1988). Thereafter, total hemoglobin 8  concentration (tHb) can be calculated by summing O2Hb and HHb. The modified Beer-Lambert Law is given by  ODλ= ɛλcLB+ OD R,λ where ODλ is the optical density of the medium, ɛλ the extinction coefficient of the chromophore, c the concentration of the chromophore, L the distance between light entry and exit point, B a dimensionless pathlength correction factor that is also called the differential pathlength factors (DPF) and OD R,λ reflects the oxygen-independent light lost due to scattering in the tissue. According to photon diffusion theory, TSI is defined as the ratio of kO2Hb to (KO2Hb+ KHHb) multiplied by 100, where K is the scattering coefficient (Naulaers et al., 2007; Suzuki et al., 1999).  TSI = (KO2Hb/ (KO2Hb+ KHHb)) * 100. Near-infrared spectroscopy measurement validity Several studies have validated NIRS to measure muscle oxygenation. One study showed a strong correlation between NIRS measurement of muscle oxygenation and mixed venous oxygen saturation during forearm exercise (Mancini et al., 1994). Other studies have Fig.1.1 A schematic view of a NIRS probe penetrating a biological tissue NIRS Near-infrared beam       Capillaries network Adipose tissue Muscle Skin 9  validated NIRS to measure blood flow against strain gauge plethysmography (Homma, Eda, Ogasawara, & Kagaya, 1996; Van Beekvelt, Colier, Wevers, & Van Engelen, 2001). NIRS measures blood flow by either the venous occlusion technique or indocyanine green dye (ICG) infusion, a light-absorbing trace. During venous occlusion technique, NIRS estimates blood flow by gauging the change in tHb over the first few seconds of occlusion  (Homma et al., 1996; Van Beekvelt et al., 2001), whereas when NIRS is applied in combination with (ICG), blood flow is determined as the ratio of ICG accumulated to the amount of ICG administered over a specific period of time (Habazettl et al., 2010; Guenette et al., 2008). Near-infrared spectroscopy applications for muscles NIRS has been applied to study muscle oxygenation and hemodynamics at different conditions including at rest (Boushel et al., 2001; Podbregar & Mozina, 2007; Wolf et al., 2003), during exercise (Bhambhani, 2004; Ferrari, Muthalib, & Quaresima, 2011; Gurley, Shang, & Yu, 2012;  Sako et al., 2001) and during surgery (Moritz, Kasprzak, Arlt, Taeger, & Metz, 2007; Murphy et al., 2010; Ono, Zheng, Joshi, Sigl, & Hogue, 2013). Muscle oxygenation has been examined in many health conditions including heart failure (Lanfranconi et al., 2006; Podbregar & Mozina, 2007;  Scheeren, Schober, & Schwarte et al., 2012), peripheral vascular disease (McCully, Halber, & Posner, 1994; Vardi & Nini, 2008), COPD (Okamoto, Kanazawa, Hirata, & Yoshikawa, 2003; Reid et al., in press; Vogiatzis et al., 2010) and mitochondrial myopathies (Abe et al., 1997; Bank & Chance, 1994). Numerous studies have documented the feasibility of NIRS technology to assess dynamic changes in tissue oxygenation and hemodynamics in a variety of age groups including fetal (Mozurkewich & Wolf, 2009), neonatal (Tortoriello et al., 2005), children 10  (Moalla, Dupont, Berthoin, & Ahmaidi, 2005) and adult (Terakado et al., 1999). Recently, there has been considerable interest in utilizing NIRS to study the patterns of muscle oxygenation and blood flow under hypoxic (Perrey & Rupp, 2009; Subudhi, Dimmen, & Roach, 2007) and hyperoxic circumstances (Orbegozo Cortés et al., 2014; Prieur, Dupont, Blondel, & Mucci, 2012).  Changes in quadriceps oxygenation and blood flow have been examined during both dynamic and static conditions. Studies showed that constant submaximal cycling exercise did not elicit quadriceps deoxygenation (Athanasopoulos et al., 2010; Nielsen et al., 2001; Turner et al., 2013). There is also evidence that suggests that quadriceps oxygenation remains constant during resting hyperpnea (Keramidas, Kounalakis, Eiken, & Mekjavic, 2010; Vogiatzis et al., 2009) and cycling at a submaximal rate with moderate resistive breathing (Nielsen et al., 2001; Turner et al., 2013). Yet, locomotor muscle deoxygenation has been noted during maximal exercise (Turner et al., 2013) and cycling with heavy resistive breathing (Nielsen et al., 2001). In addition to muscle oxygenation, the change in blood volume and flow has been assessed. Blood volume of a locomotor muscle showed a progressive decrease during incremental ITL (Shadgan et al., 2011) but not during resting hyperpnea (Keramidas et al., 2010). Because tHb is a surrogate measure of blood volume, some investigators used NIRS-ICG to precisely measure blood flow to correlate this metric with respiratory muscle work.  A previous study revealed that quadriceps blood flow remained unchanged during hyperpnea at 30, 55 and 75% of maximal minute ventilation (VEmax) (Guenette et al., 2008). This finding is consistent with Vogiatzis et al. (2009) in which stable quadriceps blood flow was observed during hyperpnea at 60, 80, 90 and 100% of maximal work rate 11  (WRmax). This may be attributed to the absence of diaphragm fatigue and the increase in cardiac output. Hence, cardiac output meets the increasing oxygen demand and prevents muscle from becoming deoxygenated. However, inadequate cardiac output, reducing blood flow to exercising muscles and the deoxygenation of respiratory and locomotor muscles may limit exercise performance at WRmax. However, during graded cycling exercise, quadriceps blood flow progressively increased up to 60% WRmax (Habazettl et al., 2010; Vogiatzis et al., 2009). Thereafter, blood flow significantly declined during submaximal and maximal exercise stages (above 80% of WRmax) (Habazettl et al., 2010; Henderson et al., 2012; Vogiatzis et al., 2009). When subjects performed constant cycling exercise with expiratory muscle loading, quadriceps blood flow was lower than its value during constant cycling (Athanasopoulos et al., 2010). Collectively, during exercise, the influence of increased respiratory muscle work on locomotor blood flow appears to be intensity-dependent. As exercise intensity and duration increases, blood flow to the locomotor muscle can decline, prioritizing the respiratory muscles.  The phenomenon of redistribution of blood flow from locomotor muscles to respiratory muscles during diaphragm fatiguing conditions is referred to as respiratory metaboreflex (Sheel et al., 2001). Metaboreflex is mediated by sympathetic nerve activity that results in vasoconstriction and increases vascular resistance in locomotor muscles when the diaphragm reaches its activation threshold (Dempsey, Romer, Rodman, Miller, & Smith, 2006; Sheel et al., 2001; Sheel, Derchak, Pegelow, & Dempsey, 2002;  St Croix, Morgan, Wetter, & Dempsey, 2000; Wetter, Harms, Nelson, Pegelow, & Dempsey, 1999). It has been hypothesized that metaboreflex occurs during sustained whole body exercise at intensities more than 85% of maximal oxygen consumption VO2max (B. Johnson, Babcock, 12  Suman, & Dempsey, 1993). Also, it has been proposed that diaphragmatic fatigue is manifested by a decline in diaphragm force production by 25 to 40% (Sheel et al., 2001; Vogiatzis et al., 2008). Respiratory muscle metaboreflex has been evaluated during maximal and submaximal exercise (Dempsey et al., 2006) and during voluntary hyperpnea against inspiratory resistance (St Croix et al., 2000; Sheel et al., 2001, 2002).  NIRS technology has unique advantages: it is non-invasive, relatively inexpensive, portable and harmless; employs non-ionizing radiation, does not cause skin burns even with extended application, is easy to use, provides continuous high-quality temporal and spatial resolution image and is more comfortable for subjects than invasive methods such as biopsies and arterial blood punctures or stabs (Boushel et al., 2001; Gurley et al., 2012; Mancini et al., 1994; Quaresima, Lepanto, & Ferrari, 2003). Quantifying blood flow with NIRS-ICG is considered minimally invasive as it requires venous cannulation. Although, ICG administration is described to be safe, adverse effects such as allergic reactions can rise (Speich, Saesseli, Hoffmann, Neftel, & Reichen, 1988). Respiratory muscle oxygenation and hemodynamics Respiratory muscles, just like other skeletal muscles, experience a progressive increase in oxygen demand with an increase in workload. Despite the considerable volume of literature that has been published on peripheral muscle oxygenation, there have been relatively few studies on respiratory muscle oxygenation in healthy subjects as well as in subjects with chronic illnesses. NIRS has been applied to determine the change in respiratory muscle oxygenation and hemodynamics during different exercise protocols. Serratus anterior and intercostal 13  muscles are the most studied muscles regarding their oxygenation during exercise. In healthy subjects during maximal incremental exercise, O2Hb and tHb of the serratus anterior muscle dropped significantly (R. Legrand et al., 2007). Conversely, Cannon et al. (2007) did not find differences in serratus anterior O2Hb and TSI during maximal incremental exercise when subjects’ arms were relaxed. The discrepancy between the studies could be attributed to differing study designs. In athletes, serratus anterior showed an increase in HHb with no significant difference in O2Hb and tHb during cycling exercise at a constant workload of 80% of VO2 max while breathing against moderate to heavy resistive inspiratory load (Turner et al., 2013). However, at maximal exercise, serratus anterior HHb increased, O2Hb decreased and tHb did not change (Turner et al., 2013). Furthermore, two studies reported that in people with chronic heart failure (CHF), the serratus anterior O2Hb and tHb decreased at lower workload at the end of the incremental cycle exercise compared with healthy subjects (Mancini et al., 1991; Terakado et al., 1999). Moreover, in children, the deoxygenation of serratus anterior during incremental exercise has been documented (Moalla et al., 2005). It appears from the aforementioned investigations that muscle oxygenation is affected by exercise intensity, health status and body position.  Several studies have reported that intercostal muscles did not deoxygenate during constant leg exercise (Athanasopoulos et al., 2010), ITL (Shadgan et al., 2011), resting hyperpnea (Keramidas et al., 2010; Vogiatzis et al., 2009) and incremental cycling exercise with mild and moderate inspiratory resistance in adults (Nielsen et al., 2001). However, intercostal HHb increased and TSI decreased during constant leg exercise with expiratory loading 14  (Athanasopoulos et al., 2010) and during incremental exercise with heavy inspiratory resistance (Nielsen et al., 2001).  Sternocleidomastoid (SCM) oxygenation has been studied during incremental ITL (Shadgan et al., 2011) and during voluntary hyperpnea (Katayama et al., 2015) in healthy males. In both conditions, SCM deoxygenated regardless of how muscle was loaded. However, the pattern of it deoxygenation was different. Incremental ITL is characterized by a progressive increase in SCM HHb that is correlated to increased load (Shadgan et al., 2011). On the other hand, SCM deoxygenation was only observed at the onset of the hyperpnea test, which may be attributed to the constant nature of loading during this test (Katayama et al., 2015). Of particular interest, a recent study of stable, moderate-to-severe COPD patients demonstrated the inability to maintain O2Hb levels in SCM even when pulse oximetry showed acceptable SpO2 levels (Reid et al., in press). It was postulated that the drop in regional O2Hb levels in the sternocleidomastoid might be due to the lower SpO2 or the inadequate redistribution of the circulation to meet the demands of the exercising muscle. Altogether, the pattern of respiratory muscle oxygenation during exercise is influenced by health status, age, exercise protocol and muscle properties. Measuring respiratory muscle blood flow is difficult due to their complex anatomical arrangement, their extensive blood supply and the heterogeneity in muscle activation across various ranges of ventilatory work. However, NIRS-ICG provides an accurate measure of respiratory muscle blood flow. Guenette et al. (2008) were the first group to examine respiratory muscle with the NIRS-ICG technique. This study was followed by a number of investigations that examined respiratory muscle blood flow in different conditions. Most of the published studies that examined blood flow to respiratory muscles 15  have simultaneously examined blood flow to the locomotor muscle. Interestingly, blood flow was mostly obtained from the 7th intercostal and quadriceps muscles of highly active individuals. During hyperpnea at different levels of minute ventilation (VE), intercostal blood flow increased progressively in line with increased work of breathing (Guenette et al., 2008; Vogiatzis et al., 2009). In addition, it has been reported that not only did intercostal muscle blood flow increase linearly during isocapnic hyperpnea, but SCM blood flow increased as well (Guenette et al., 2011). Moreover, similar trends of increasing blood flow to the intercostal muscle were illustrated during graded incremental cycling exercise up to 60% of VO2max (Habazettl et al., 2010) and during constant cycling with expiratory muscle loading (Athanasopoulos et al., 2010). Henderson et al. (2012) examined the effect of incremental exercise on intercostal blood flow. They concluded that there was a lack of increase in intercostal blood flow. It has conclusively been shown that blood flow distribution is closely dependent on exercise protocols. 1.1.5 Electromyography Detecting the myoelectrical manifestation using EMG had been difficult until the beginning of the 20th century. The foundation of the use of EMG began in the 1930s; Adrian and Bronk (1929) introduced the use of concentric needle electrodes. The application of EMG on respiratory muscles have been started around the mid-twentieth century. Campbell is one of the earliest investigators who examined the contribution of abdominal muscles to ventilation in humans (Campbell & Green, 1953; Campbell, 1952, 1957). Also, other investigators have examined the activity of other respiratory muscles like diaphragm (Guslits, Gaston, Bryan, England, & Bryan, 1987; Lourenço & Mueller, 1967; Lourenço, 1969), intercostal (De Troyer & Sampson, 1982; Green & Howell, 1959; 16  Homma & Eklund, 1978) and sternocleidomastoid (Gronbaek & Skouby, 1960; Raper, Thompson, Shapiro, & Patterson, 1966). With the continuous development in EMG technology, EMG is now used not only as a diagnostic tool but also as a biofeedback tool. There is a wealth of literature on EMG application to evaluate muscle activation, recruitment, fatigue and neural drive. EMG has been applied to most of the skeletal muscles in many conditions. In sports medicine and rehabilitation, EMG is widely utilized to analyze gait and posture, assess musculoskeletal and neuromuscular pathologies, monitor patients’ improvement and guide exercise prescription (Giggins, Persson, & Caulfield, 2013; Shenoy, 2010). Basically, EMG measures the myoelectrical manifestation of the excitation process of the motor units provoked by action potential propagation along the length of muscle fibers during voluntary concentric contraction  (Rouffet & Hautier, 2008; Von Tscharner, Goepfert, & Nigg, 2003), voluntary isometric contractions (Ravier, Buttelli, Jennane, & Couratier, 2005; Youn & Kim, 2010), and involuntary contraction via electrical or magnetic stimulation (Millet et al., 2012; Rossini et al., 2015). However, evaluating respiratory muscle activation can be a challenging task because of the anatomical orientation of these muscles and the potential technical limitations of EMG (Mancini et al., 1991; Hawkes, Nowicky, & McConnell, 2007). Type of electromyographic electrodes To assess muscle recruitment and fatigue, there are two main EMG techniques. One is the intramuscular EMG technique in which needle electrodes are applied. Intramuscular EMG has been described as an invasive procedure, unpleasant for the participants, requiring high 17  skills to perfectly place needles and yielding limited information from few motor units. All in all, these factors limit their use in clinical settings (Chiti et al., 2008; Gibson et al., 2002). However, it has been applied on superficial respiratory muscles such as scalene (SA) (Hug et al., 2006; Yokoba, Abe, Katagiri, Tomita, & Easton, 2003), SCM (De Troyer, Peche, Yernault, & Estenne, 1994; Hudson, Gandevia, & Butler, 2007) and intercostals (Chiti et al., 2008; De Troyer et al., 1994; Gandevia, Hudson, Gorman, Butler, & De Troyer, 2006). Due to the potential risk of pneumothorax, diaphragm activity has rarely been measured with intramuscular electrodes (Saadeh, Crisafulli, Sosner, & Wolf, 1993). Another method to obtain EMG signals is the surface EMG (sEMG). sEMG is the most favorable and easiest EMG technique for clinicians (Gibson et al., 2002; Hakkinen & Komi, 1983). Over the past decades, several studies have assessed the myoelectrical manifestation of respiratory muscles in healthy individuals (Hawkes et al., 2007; Nadiv et al., 2012; Shadgan et al., 2011) and patients (Duiverman et al., 2009; Mañanas, Jané, Fiz, Morera, & Caminal, 2000) using sEMG. There are, however, certain limitations that might influence the interpretation of sEMG findings.  The most noticeable limitations of sEMG are related to motion artifacts, signal contamination, and electrode placement. Motion artifacts often appear when EMG data are collected during dynamic exercise as a function of time. Artifacts are strongly associated with skin stretching and loss of contact due to sweating (Criswell, 2011). EMG signals of respiratory muscle might become contaminated by signals initiated from adjacent muscles, this phenomenon is known as crosstalk (Sinderby, Friberg, Comtois, & Grassino, 1996). Thus, having small interelectrode distance is recommended to improve the signal quality by minimizing the influence of crosstalk (Farina, Merletti, Indino, Nazzaro, & Pozzo, 18  2002). When diaphragm EMG is obtained, for instance, the interelectrode distance is suggested to be less than 2 cm (Glerant et al., 2006). Aside from motion artifacts and crosstalk, it is well known that appropriate positioning of electrodes is essential to record accurate high-quality EMG signals (Duiverman et al., 2004). This can be achieved merely by identifying motor unit action potentials and placing the electrodes away from the innervation zones (Merletti, Rainoldi, & Farina, 2001). On the other hand, both bipolar surface EMG and intermuscular EMG afford limited local information. Also, neither bipolar surface EMG nor intermuscular EMG permits the recognition of the innervation zones.  Recent investigations provide strong and reliable evidence for the usefulness of multi-channel EMG to detect a number of motor unit action potentials and precisely measure the conduction velocity (Falla, Dall’Alba, Rainoldi, Merletti, & Jull, 2002; Merletti, Farina, & Gazzoni, 2003). Multi-channel EMG provides comprehensive insight about the myoelectrical manifestation of large muscles with respect to the huge number of motor units. The necessity to examine the entire muscle bulk contributes to large inter-individual variation in muscle architecture. However, the number of detectable motor units depends upon the number of channels being used. For example, more than 83% of motor units from the abductor digiti minimi muscle were detected by 81-channel EMG electrodes, whereas fewer than 4% were recorded by a single monopolar channel (Farina, Negro, Gazzoni, & Enoka, 2008). Moreover, multi-channel EMG has the potential to abate the influence of the innervation zone on EMG estimates (Smith et al., 2015). In addition, estimation of muscle fatigue based on median frequency was more pronounced if assessed via multi-channel electrodes than in simulated bipolar electrodes (Gallina, Merletti, & Vieira, 2011). 19  Also, crosstalk has been postulated to be minimized with this technique (De Luca, Kuznetsov, Gilmore, & Roy, 2012). Figure 1.2 illustrates an example of EMG signal obtained by linear array EMG electrode. Despite the extensive literature exploring the strong theoretical rationale, advantages and the application of multi-channel EMG, currently, sEMG is still predominantly used both in ergonomics and in rehabilitation. The reason behind this low popularity extends to the complexity of the associated data extraction technique and analysis processes since a large numbers of channels are used (Gazzoni, 2010). Nevertheless, over the past 30 years, diaphragm activity has been recorded via multiple esophageal electrodes catheter (Daubenspeck, Leiter, McGovern, Knuth, & Kobylarz, 1989; Sinderby, Beck, Lindström, 5mm Axon of motor neuron 67.82 67.83 67.84 67.85 67.86 67.87 67.88 67.89 67.9 67.91 67.92123456SCM MU, MIP after, MaxVal: 940.32Channels (number)Time (s)67.82 67.83 67.84 67.85 67.86 67.87 67.88 67.89 67.9 67.91 67.92123456SCA MU, MIP after, MaxVal: 726.55Time (s)Alpha motor neuron Muscle fiber Linear array electrode Time (s)       Innervation zone EMG amplitude (mV) Fig.1.2 Schematic presentation of acquired EMG signals by linear array electrode 20  & Grassino, 1997). However, this technique has a potential risk of aspiration, bradycardia, and regurgitation. In addition, it is an unpleasant procedure for subjects (Gibson et al., 2002). The reliability and validity of esophageal EMG are well established in both healthy subjects (Reilly et al., 2013) and patients (Jolley et al., 2009). Of note, multi-channel EMG has been used on SCM and SA as neck flexor muscles to investigate the etiology of neck pain (Falla, Jull, Rainoldi, & Merletti, 2004).  Regardless of EMG detecting technique, respiratory muscle recruitment patterns have been studied during tidal breathing (De Troyer & Estenne, 1984; Gandevia et al., 2006; Hug et al., 2006), pursed-lip breathing (Breslin, 1992), static ventilatory efforts (Hudson et al., 2007; Yokoba et al., 2003) and exercise. According to A. Legrand and colleagues (2003), SA has a greater mechanical advantage than SCM, which has been determined by measuring the fractional change in muscle length using computer tomography. Particularly, muscles with higher mechanical advantage are activated earlier than those with lower mechanical advantage. The matching between muscle neural drive to a muscle and its mechanical advantage are known as the neuromechanical matching principle (Butler, De Troyer, Gandevia, Gorman, & Hudson, 2007). This has been supported by several studies that reveal that early SA activation appears at the beginning of static inspiratory tasks, whereas the activation of SCM was delayed until 9 to 20% of MIP (Hudson et al., 2007; Yokoba et al., 2003). Similarly, the activation of intercostal muscle is inhomogeneous. De Troyer, A. Legrand, Gevenois, and Wilson (1998) have investigated the distribution of the mechanical advantage of intercostal muscles during tidal breathing. They found that the intercostal muscle at the fifth intercostal space was four times lower in mechanical advantage than the one at the second intercostal space. Also, they posed a 21  question regarding whether the onset time of inspiratory phasic activity is parallel to the mechanical advantage. Subsequently, it was shown that intercostal mechanical advantage is in accordance with the rostrocaudal distribution of the inspiratory neural drive (Gandevia et al., 2006; Hudson et al., 2007).  During exercise, respiratory muscle recruitment occurs in response to increased loading. Therefore, exercise intensity and pulmonary ventilation are important factors to determine the extent of recruitment pattern and the incidence of fatigue. Numerous studies have attempted to compare the diaphragm to other inspiratory muscle activation during breathing exercise in healthy adults.  Nobre et al. (2007) investigated the effect of ITL that progressed from 10 to 30 cmH2O in young healthy individuals. They did not find a significant difference in RMS of SCM during ITL. Also, in the same age group, SCM was not active during an inspiratory load of 15% of MIP (Chiti et al., 2008). Moreover, SCM does not appear to be recruited at inspiratory load that is equivalent to 30% of MIP in healthy elderly subjects (De Andrade et al., 2005). On the other hand, during heavier loading exercise such as incremental ITL that progressed up to 108 cmH2O, the amplitude of SCM increased significantly at 70% of ITL duration (Shadgan et al., 2011).  Previous studies have shown that monitoring intercostal EMG is clinically relevant to evaluate the change in inspiratory load and ventilatory mechanics for patients with cystic fibrosis and COPD during an exacerbation stage (Murphy et al., 2011; Reilly, Jolley, Elston, Moxham, & Rafferty, 2012). In several pathological conditions that present with diaphragm weakness, SCM muscles are highly recruited (Parthasarathy, Jubran, Laghi, & Tobin, 2007; Peche et al., 1996; Similowski et al., 2000). When healthy subjects progressively increase their ventilatory efforts, an early activation of  SCM and intercostals 22  muscles was observed (A. Legrand, Schneider, Gevenois, & De Troyer, 2003; Saboisky, Gorman, De Troyer, Gandevia, & Butler, 2007). During incremental exercise test, COPD patients demonstrated earlier and greater intercostal and SA activation than healthy subjects (Duiverman et al., 2009). 1.1.6 Gas exchange during exercise Pulmonary gas exchange is highly efficient in healthy subjects at rest. This efficiency can be altered by illnesses such as COPD, interstitial lung disease, asthma and diabetes mellitus (Peltonen et al., 2012; Young & Bye, 2011). Moreover, high altitude and exercise are other factors that may influence gas exchange and impair physical performance. This topic has been investigated extensively in scenarios where independent factors and interaction between factors have been examined.  At sea level, the normal range of the PaO2  is between 80 to 100  mmHg, and the PaCO2 is 35 to 45 mmHg (Hall & Guyton, 2015). However, when the pulmonary system partially fails to cope with increasing carbon dioxide production (VCO2) and oxygen consumption (VO2), it results in arterial hypoxemia. The degree of arterial hypoxemia is affected by general health status, lung function, fitness, and exercise intensity and duration (Romer, Haverkamp, Lovering, Pegelow, & Dempsey, 2006). Several mechanisms have been postulated to illustrate the potential etiology of arterial hypoxemia including hypoventilation, pulmonary shunt, diffusion limitation, and ventilation-perfusion mismatching. Moreover, arterial hypoxemia appears not only with lung disease but also during exercise. This phenomenon has been termed as exercise-induced arterial hypoxemia (EIAH). According to a definition provided by Dempsey and Wagner (1999), 23  EIAH is a reduction in PaO2 or SpO2 level during any point of exercise to below pre-exercise level. EIAH can be classified according to the level of severity as mild, moderate, and severe. The acceptable range of SpO2 in mild EIAH is between 93 to 95%, moderate is 88 to 93%, and below 88% is considered to be severe EIAH (Dempsey & Wagner, 1999).  1.1.7 Causes of arterial hypoxemia Pulmonary gas exchange defect result in arterial hypoxemia which may occur because of one or more pathophysiological mechanisms. First, hypoventilation is a condition involving an inappropriate reduction in alveolar ventilation. Hypoventilation can be determined from arterial blood gas analysis as indicated by an increase in PaCO2 above the normal values (Mahendradhata & Moerman, 2004). Second, pulmonary shunt occurs when a fraction of venous blood passes through the lung without gas exchange. Patients with obstructive airway diseases and some cardiac patients may develop hypoxemia as a consequence of pulmonary shunt (Mahendradhata & Moerman, 2004). Third, diffusion limitation which is defined as a reduction in the ability of the oxygen and the CO2 to diffuse through the alveolar capillary membrane due to a decrease in the surface area, an increased thickness of the membrane or a decline in diffusion time. Gas diffusion occurs passively based on gas concentration differences across the membrane. In the case of interstitial lung disease, diffusion limitation affects the ability of oxygen transport through the capillaries and becomes aggravated with exercise because of a reduction in pulmonary capillary transit time (Mahendradhata & Moerman, 2004). Fourth, ventilation-perfusion mismatching results from either an increase in ventilation without any compensation in cardiac output or a decrease in blood flow while ventilation remains steady. Ventilation-perfusion mismatching could develop during submaximal exercise in healthy subjects 24  (Hopkins, 2006; Hammond, Gale, Kapitan, Ries, & Wagner, 1986).  The balance between the extraction of CO2 from the capillaries into the alveoli and the reverse direction of oxygen from the alveoli to the capillaries is known as diffusion equilibrium. For healthy subjects at rest, the distribution of ventilation-perfusion ratio (VA/Q), which is the ratio of alveolar ventilation to cardiac output, is constant at a value of approximately 1 (Brown, Miller, & Eason, 2006). During mild and moderate exercise, subjects may hyperventilate spontaneously to compensate for the metabolic acidosis and thereby regulate acid-base balance; this results in an increase in PaO2 and a reduction of  PaCO2 (Stickland, Lindinger, Olfert, Heigenhauser, & Hopkins, 2013). VA/Q may be altered during peak incremental exercise and heavy exercise in normoxia. A greater mismatching has been observed with exercise at high altitudes in young, healthy men (Torre-Bueno, Wagner, Saltzman, Gale, & Moon, 1985). With ventilation-perfusion mismatching, the body fails to counterbalance the declining PaO2 of more than 10 mmHg and SpO2 of more than 5% from the rest. With hypoxic exercise at high altitudes, not only does ventilation-perfusion mismatching contribute to EIAH, but diffusion limitation also has a major influence as well (Wagner et al., 1986). 1.1.8 Types of hypoxia The natural atmospheric air is composed of a mixture of gases. Nitrogen and oxygen are the main components; representing 99% of the total gas concentration (i.e. nitrogen ~78.08% and oxygen 20.95%) (Thiriet M, 2014). The partial pressure of oxygen (PO2) is dependent on two elements: the fractional concentration of oxygen and the barometric pressure. A decline in PO2 results in either hypobaric hypoxia or normobaric hypoxia. 25  Hypobaric hypoxia occurs when the PO2 decreases in response to decreasing barometric pressure below 760 mmHg, whereas normobaric hypoxia contributes to a reduction in the fractional concentration of inspired oxygen (FIO2) below the ambient air (FIO2=20.9%). A good example of hypobaric hypoxia could occur for those who live in a high altitude zone. With advanced technology, hypoxia can be simulated in laboratories using either an environment chamber to modify pressure or a gas mixture that consists of a low FIO2. Hypoxia exemplifies a valuable experimental model to examine the role of oxygen availability on cardio-respiratory response and reduced muscle function induced by lung disease or exercise. Acute cardio-respiratory response to hypoxia at rest At rest, chemoreflex activation results in an increase in sympathetic activity, heart rate (HR), arterial blood pressure and VE to maintain adequate blood flow and alveolar ventilation (Guimarães, Belli, Bacal, & Bocchi, 2011). Cooper et al. (2005)  investigated the interactions of chemoreceptors and baroreceptors reflexes by hypoxia in healthy adults. They found that breathing a hypoxic gas of 12% FIO2 caused a deterioration in end-tidal oxygen pressure (PETO2) and SpO2 from 110 + 1.7 to 58.7 + 2.5 mmHg and 98.3 + 0.3% to 88.8 + 1.1%, respectively. Also, HR increased significantly without any distinctive effect on arterial blood pressure (Cooper et al., 2005). The pattern of alteration in HR is consistent with another investigation on the immediate responses to normobaric hypoxia (Holloway et al., 2011). In severe hypobaric hypoxia, both HR and blood pressure increased during rebreathing tests (Ainslie & Burgess, 2008). After the removal of hypoxic stimuli, HR returned to the baseline measure within 30 minutes (Holloway et al., 2011).  26  A recent comprehensive study examined the acute and chronic cardio-respiratory response in young men when exposed to normobaric hypoxia (pressure=760 torr, FIO2=10.5%), hypobaric hypoxia (pressure=427 torr, FIO2=19.8), hypobaric normoxia (pressure=427 torr, FIO2=39.5) and normobaric normoxia (pressure=760 torr, FIO2=20.9) inside an environmental chamber for six hours. This study revealed no significant difference between both hypoxic conditions regarding HR, SpO2, tidal volume (VT),  breathing frequency (fb), and VE. HR increased significantly during hypoxic conditions when compared with normoxic conditions after five hours. VT was only greater during the first five minutes of the hypoxic relative to the normoxic condition. VE rapidly increased and was significantly higher at five minutes during hypobaric hypoxia and normobaric hypoxia than during normobaric normoxia. The increase in VE was followed by a gradual decrease for approximately an hour before it increased again. Consequently, SpO2 showed a progressive drop for the first 30 minutes when it reached the minimum value (Richard et al., 2014). It has been suggested that breathing room air for 15 to 60 minutes is required in order to achieve a complete ventilatory recovery after sustained isocapnic hypoxic breathing test (Easton, Slykerman, & Anthonisen, 1988). Acute cardio-respiratory response to hypoxia during exercise Previous research findings into the cardio-respiratory response to acute hypoxia have been inconsistent. Several authors observed a lower HR at maximal hypoxic exercise in trained and untrained subjects compared with  maximal normoxic exercise (Benoit, Busso, Castells, Geyssant, & Denis, 2003; Calbet et al., 2003; Mollard et al., 2007; Ofner et al., 2014; Woorons, Mollard, Lamberto, Letournel, & Richalet, 2005). However, others did not notice a difference between hypoxic and normoxic maximal exercise  (Kennedy et al., 27  2008; Ivamoto et al., 2014; Zattara-Hartmann and Jammes, 1996). At submaximal hypoxic exercise and hypoxic hyperpnea, many authors reported higher HR (Katayama et al., 2015; Sandoval & Matt, 2002; Taylor & Bronks, 1996) although some studies showed either lower or equal HR during submaximal hypoxic exercise compared with normoxic exercise (Calbet et al., 2003; Vogiatzis et al., 2008). Regarding VE, studies have shown that exercise protocol has a significant influence on VE response to a hypoxic stimulus. For instance, VE was significantly lower at WRmax of normoxic maximal exercise than during hypoxic test (Calbet et al., 2003; Ofner et al., 2014). In addition, breathing a hypoxic gas mixture had no effect on VE during hyperpnea (Katayama et al., 2015; Verges, Bachasson, & Wuyam, 2010). Moreover, most of the studies revealed that performing hypoxic exercise reduced the VO2max at different hypoxic dose and exercise intensity (Calbet et al., 2003; Fukuda et al., 2010; Ofner et al., 2014). However, trained subjects had greater VO2max decline than untrained subjects (Martin & O’Kroy, 1993; Woorons et al., 2005). Compared to values attained during normoxia, PaO2 and PaCO2 were significantly different during hypoxia not only at maximal exercise but also at submaximal exercise  (Katayama et al., 2013; Vogiatzis et al., 2008; Zattara-Hartmann & Jammes, 1996). Of interest, trained men and women, experience a greater reduction in SpO2 and HR than untrained subjects during maximal hypoxic exercise. (Martin & O’Kroy, 1993; Mollard et al., 2007; Peltonen, Tikkanen, & Rusko, 2001; Woorons et al., 2005). Furthermore, some athletes reach a hypoxemic level even at sea level during maximal exercise test (Grataloup, Busso, Castells, Denis, & Benoit, 2007; Woorons et al., 2005). It is generally accepted that SpO2 is negatively correlated with physical fitness during exercise (Mollard et al., 2007). The 28  coordination between cardiac output and ventilation has a beneficial physiological role in preventing further arterial desaturation and, more importantly, protecting the heart from myocardial ischemia during hypoxia (Grataloup et al., 2007; Peltonen et al., 2001). Muscular response to hypoxia Breathing a hypoxic gas mixture poses a challenge to deliver sufficient oxygen to tissues. However, existing evidence supports the absence of muscle deoxygenation during acute exposure to hypoxia at rest despite the significant fall in SpO2 (Katayama et al., 2015; Rupp & Perrey, 2009). Many studies have reported similar magnitude of limb muscle deoxygenation during normoxic and hypoxic submaximal exercise (DeLorey, Shaw, Shoemaker, Kowalchuk, & Paterson, 2004; Peltonen et al., 2009), isometric exercise (Gomes, Matsuura, & Bhambhani, 2013; Katayama, Yoshitake, Watanabe, Akima, & Ishida, 2010) and incremental exercise (Bowen et al., 2013). However, others reported greater muscle deoxygenation during incremental hypoxic exercise (Osawa, Kime, Hamaoka, Katsumura, & Yamamoto, 2011; Subudhi, Dimmen, & Roach, 2007). Since there are contrasting findings, investigators have pointed out a number of explanations. First, Katayama et al. (2010) have explored the difference between the intermittent and the sustained exercise protocols on muscle oxygenation. They found that performing intermittent exercise protocol in hypoxic condition exacerbates muscle deoxygenation, whereas sustained protocol did not. Another observation, is that the body compensates for decreased oxygen availability by increasing blood flow to the active muscles during isolated submaximal exercise which results in a comparable muscle deoxygenation during normoxic and hypoxic exercise (DeLorey et al., 2004; Koskolou, Calbet, Rådegran, & Roach, 1997).  29  Data from several sources have identified the effect of hypoxia on skeletal muscle fatigue during various conditions. EMG is utilized to detect muscle fatigue by either externally stimulating the nerve that innervates a specific muscle or by spontaneously performing maximal muscle contraction before and after an intervention. A comprehensive review paper explored the causative factors behind the discrepancies in muscular behavior in hypoxic studies (Perrey & Rupp, 2009). The authors concluded that the hypoxic response is dependent on muscle properties (oxidative capacity, muscle fiber type and blood supply), type of contraction (voluntary vs. involuntary evoked by electrical stimulation, static vs. dynamic, or sustained vs. intermittent), hypoxia characteristics (intermittent vs. continue and chronic vs. acute) and experimental design. For instance, quadriceps muscle fatigue has been studied in many exercise protocols. Studies have not shown an effect of hypoxia on quadriceps fatigue during incremental cycling exercise in moderate hypoxia (Taylor & Bronks, 1996), constant knee extension exercise (Fulco et al., 1996) and isometric knee exercise (Ivamoto et al., 2014). Although the lack of fatigue was evident in those studies, exercise time to exhaustion was markedly shorter during hypoxic than normoxic exercise. However, hypoxic intermittent leg exercise resulted in greater reduction in mean power frequency and twitch force (Amann et al., 2006;  Katayama, Amann, Pegelow, Jacques, & Dempsey, 2007; Romer et al., 2006). These findings support the statement pointed by Perrey and Rupp (2009) that muscle fatigue is dependent on the nature of the exercise. Hypoxic effects on respiratory muscle There are a plethora of studies that describe respiratory muscle fatigue during exercise. Often, respiratory muscle fatigue is examined during whole-body exercise. Nevertheless, 30  some researchers draw their conclusions based on breathing exercise interventions. Accordingly, there are relatively fewer data available in the literature on the effect of hypoxia on respiratory muscle performance. To assess the effect of hypoxia on inspiratory muscle fatigue, some studies have used inspiratory resistive exercise, whereas others have used a hyperpnea breathing test or whole-body exercise. Breathing a hypoxic gas of an FIO2 equal to 13% during inspiratory resistive exercise, accelerated diaphragm and intercostal muscle fatigue, which was confirmed by a significant fall in EMG frequency (Jardim et al., 1981). Others reported a negative association between diaphragm and scalene activity and SpO2 during a severe isocapnic hypoxic rebreathing test (Xie, Takasaki, & Bradley, 1993). One of the early investigations explored the difference between inspiratory and expiratory muscle recruitment in healthy men during hyperoxic hypercapnia and isocapnic hypoxic tests (Takasaki, Orr, Popkin, Xie, & Bradley, 1989). This study showed that in healthy subjects, diaphragm was highly activated by hypoxia, whereas the contribution of expiratory muscles was greater in response to hypercapnia. A unique aspect of one study is that the investigators titrated the hypoxia level based on arterial oxygen saturation (80%) instead of using a fixed FIO2 to evaluate the effect of hypoxia on inspiratory (diaphragm) and expiratory muscle (abdominal) during hyperpnoea breathing in healthy adults (Verges et al., 2010). It revealed that at rest, the transdiaphragmatic and gastric twitch pressure produced by cervical and thoracic magnetic stimulation did not differ when breathing room air or hyperoxic or hypoxic gas mixtures. Indeed, diaphragm fatigue was proven by a reduction in transdiaphragmatic and gastric twitch pressures immediately following hypoxic hyperpnea (Verges et al., 2010). This observation is in agreement with the findings 31  of Babcock et al. (1995) in which diaphragm fatigue was verified after moderate hypoxic submaximal exercise. These observations in healthy subjects are consistent with those observed in athletes (Vogiatzis et al., 2007).  With certainty, Vogiatzis et al. (2007) designed their experiment to maintain the respiratory muscle work to be identical with different FIO2 concentrations in order to limit the impact of hyperventilation. They found that diaphragm force production at 10 minutes recovery was lower in mild and moderate hypoxic exercise than normoxic submaximal exercise (Vogiatzis et al., 2007). In spite of this, hypoxia showed no effect on pressure time product of the diaphragm during submaximal exercise (Vogiatzis et al., 2007) and on inspiratory mouth pressures during a 10-minute maximal inspiratory breathing test (Ameredes & Clanton, 1989). To the best of our knowledge, there are only two published works that have described the effect of hypoxia on respiratory muscle oxygenation and blood flow during exercise in humans. Vogiatzis et al. (2008) have questioned whether the limited blood flow to respiratory muscles exaggerates diaphragm fatigue during hypoxic exercise in trained subjects. Blood flow to intercostal muscle was examined during normoxic and hypoxic constant cycling exercise. The work of breathing was matched between conditions. Their findings confirmed a lack of an increase in cardiac output and intercostal blood flow during hypoxic exercise. Therefore, it has been proposed that the mismatching between blood flow and oxygen supply could justify the greater diaphragm fatigue that is induced by hypoxic exercise. The second investigation provides strong evidence that SCM and intercostal muscles (at the sixth intercostal space) are prominently deoxygenated and recruited during severe hypoxic isocapnic hyperpnea test compared with normoxic 32  isocapnic hyperpnea test using NIRS and surface EMG (Katayama et al., 2015). The deoxygenation was demonstrated not only by an increase in HHb concentration, but by a reduction in TSI as well (Katayama et al., 2015). In addition, the EMG amplitude of SCM was greater during hypoxic hyperpnea than normoxic hyperpnea. Furthermore, due to the scarcity of the literature on the acute effect of hypoxia on respiratory muscle oxygenation and recruitment, it is unknown whether hypoxic dose and experiment design provoke a different response of selective muscles.  1.1.9 Overall study rationale From the above observations, it is clear that effectiveness of the respiratory muscles is essential to survival by maintaining adequate pulmonary ventilation. However, several factors may contribute to respiratory muscle fatigue and dysfunction. Thus, many researchers have attempted to explore some of those factors by either examining patients who are known to have respiratory muscle dysfunction or by imposing a simulated stress on respiratory muscle in healthy subjects. It is well known that the diaphragm generates the highest portion of the total inspiratory pressure. Other inspiratory muscles such as scalene, intercostals, pectoralis, serratus anterior and sternocleidomastoid also contribute over a wide range of ventilation. Moreover, the activity of those extra-diaphragm muscles can be dramatically increased in chronic lung disease and chest wall disease. In the present study, we focused on three inspiratory muscles: SA, SCM and parasternal intercostal at the second intercostal space for several reasons. First, SA and parasternal intercostal muscles are obligatory inspiratory muscles that are activated in each breath at rest and during heavy ventilatory efforts (Hudson et al., 2007; Reilly et al., 2013). Second, 33  it has been suggested that monitoring intercostal activity instead of diaphragm activity can be used to estimate respiratory drive (Murphy et al., 2011; Reilly et al., 2013).  Third, previous studies showed a linear correlation between SA and SCM activity and dyspnea perception at high inspiratory load in healthy people and in intubated COPD patients (Breslin, Garoutte, Kohlman-Carrieri, & Celli, 1990; Chiti et al., 2008; Schmidt et al., 2013). Thus, monitoring inspiratory neck muscle activity could be beneficial to estimate dyspnea for critically ill patients who have communication impairments, are under sedation, or are intubated. In addition, it could be a valuable measure to assess the increase in ventilatory efforts during a weaning trial or during exercise in patients with respiratory diseases. Furthermore, due to the scarcity of the literature on the acute effect of hypoxia on respiratory muscle oxygenation and recruitment, it is unknown whether hypoxic dose and experimental design will provoke a different response for selected muscles. Thus, understanding the effect of hypoxia during ITL in healthy subjects has important implications for those with chronic respiratory disease because it allows examination of one or more factors that might contribute to reduced respiratory muscle function. Our hypoxic dose calculations were based on calculations that considered the alveolar gas equation to calculate the PAO2,  the A-a gradient and the oxygen-haemoglobin dissociation curve,  we predicted to attain a PaO2 of 41.5 mmHg or SpO2 of approximately 77%   The PAO2 was estimated from the alveolar gas equation (Curran-Everett, 2006) using an FIO2 of 15%. PAO2 = (FIO2 *( barometric pressure – water vapor pressure))- PaCO2 / respiratory quotient  52     = (0.15 * (760-47))- (44/0.8) 34  PaCO2 was determined from the mean PETCO2 value at the end of ITL from Shadgan et al. (2011) study. PAO2 = 52 mmHg as calculated from the alveolar gas equation  PaO2 was determined using the calculated PAO2 of 52 and inserting it into the following equation to estimate the A-a gradient (Marx, 2014). A-a gradient  = (age/ 4) + 4               A-a gradient = (30/4) + 4 = 11.5              PAO2 - PaO2 = 11.5    PAO2  for an FIO2 is calculated to be 52              52    - PaO2  = 11.5              PaO2  =  41.5 mmHg A mean age of 30 years was assumed for our sample of population.  SpO2 was estimated from the oxygen dissociation curve. 1.2 Objectives and hypotheses of the thesis The primary objectives and hypotheses are as follows Objective 1: to determine the feasibility of spatially resolved NIRS to quantify muscle oxygenation of sternocleidomastoid (SCM), parasternal (PS) and scalene (SA) during incremental inspiratory threshold loading (ITL) in healthy adults (Chapter Two). Objective 2: to examine the combined effect of acute normobaric hypoxia (FIO2= 15%) and incremental ITL on inspiratory muscle oxygenation (Chapter Two).  Objective 3: to compare the EMG activation and signs of fatigue from SA and SCM during normoxic and hypoxic ITL of FIO2 equal to 15% in healthy adults (Chapter Three). 35  Hypothesis 1: We hypothesized that NIRS would be a feasible non-invasive tool to measure inspiratory muscle oxygenation during incremental ITL under normoxic and hypoxic conditions (Chapter Two).  Hypothesis 2: We hypothesized that the accessory inspiratory muscle, SCM, would deoxygenate, which manifests by a progressive a decrease in TSI  prior to task failure during both ITL conditions. Furthermore, these changes would be exaggerated during hypoxic ITL (Chapter Two).  Hypothesis 3: We hypothesized that the increase in inspiratory loads would result in increased SA and SCM activation. Moreover, hypoxic ITL would accentuate EMG activity and fatigue, which, in turn, would exaggerate dyspnea perception (Chapter Three).         36  Chapter Two: Effect of acute hypoxia on inspiratory muscle oxygenation during incremental threshold loading in healthy adults 2.1 Introduction Respiratory muscle dysfunction is a primary contributor to ventilatory failure in chronic disorders such as chronic obstructive pulmonary disease (COPD). A review by Mal and Armenqaud (1988) highlighted several factors that can cause inspiratory muscle fatigue in different diseased populations. For instance in COPD, inadequate gas exchange and hypoxemia can lead to an imbalance between the oxygen supply and demand. Dubois Jamart, Machiels, Smeets, and Lulling (1994) reported that severe hypoxemia is associated with a high mortality rate in COPD patients. Thus, several investigators have examined the effect of hypoxia on respiratory muscle fatigue in both humans (Jardim et al., 1981; Verges et al., 2010; Vogiatzis et al., 2007) and animal models (Mayock, Standaert & Woodrum, 1992; Farkas, McCormick & Gosselin, 2007) to provide insight into factors contributing to ventilatory failure. These studies coupled with the work of others show that hypoxia accentuates diaphragmatic fatigue under a wide range of experimental conditions including voluntary hyperpnea (Verges et al. 2010) and whole body exercise (Babcock et al. 1995; Vogiatzis et al. 2007).  Besides hypoxemia, increased respiratory loads due to higher levels of minute ventilation, airflow limitation and a stiffer chest wall can further accentuate the energy imbalance present in COPD (Mal and Armenqaud, 1988). In extreme conditions with diaphragmatic weakness and during weaning failure, the sternocleidomastoid (SCM) showed an increase in electromyographic (EMG) activity in 83% of breaths in patients who failed weaning trials, whereas it was activated in only 19% of breaths in those who successfully weaned 37  from mechanical ventilation (Parthasarathy et al., 2007). The SCM is a key accessory muscle that becomes actively recruited to assist the primary inspiratory muscles when ventilatory loads are increased (A. Legrand et al., 2003). Thus, evaluating accessory inspiratory muscles during fatiguing conditions may provide signs of pending ventilatory failure.  Near-infrared spectroscopy (NIRS) is a non-invasive tool to assess tissue hemodynamics and has provided evidence predictive of muscle fatigue based on the attenuation in muscle oxygenation. Murthy and colleagues (2001) reported a moderate correlation between the reduction in forearm muscle oxygenation and the decrease in twitch force under ischemia. Other studies demonstrated strong-to-moderate positive correlations between tissue saturation index (TSI), oxygenated hemoglobin concentration (O2Hb) and the EMG mean power frequency during constant isometric contractions to exhaustion  (Moalla, Merzouk, Costes, Tabka, & Ahmaidi, 2006; Sayli et al. 2014; Yamada et al., 2008), whereas the TSI have been shown to be negatively associated with the EMG root mean square (Elcadi, Forsman, & Crenshaw, 2011; Taelman et al., 2011) and HHb was negatively correlated to EMG mean power frequency (Yamada et al., 2008). Therefore, deoxygenation measures provided by NIRS show deficits concurrently with EMG signs of fatigue.  To date, the studies examining respiratory muscle oxygenation have focused on either the intercostal or serratus anterior muscles (Vogiatzis et al., 2009; Cannon et al., 2007). However, recent studies provide evidence that supports further inquiry into SCM oxygenation during fatiguing conditions (Katayama et al., 2015;  Reid et al., in press; Shadgan et al., 2011). For example, O2Hb in the SCM was maintained throughout incremental inspiratory threshold loading (ITL) until task failure in healthy adults 38  (Shadgan et al., 2011) but decreased during ITL in patients with moderate-to-severe COPD (Reid et al., in press). Another study investigated inspiratory muscle oxygenation during isocapnic hyperpnea that required a low load, high velocity inspiratory and expiratory muscle contractions (Katayama et al., 2015). These investigators concluded that SCM was markedly deoxygenated during hypoxic relative to normoxic isocapnic hyperpnea in healthy men. It is not yet known whether hypoxia contributes to deoxygenation and reduced function of the respiratory muscles associated with task failure during the high load, slow velocity inspiratory muscle contractions required during incremental ITL in healthy men and women. In light of these previous observations, we aimed to impose two factors, hypoxia and external inspiratory loading, to evaluate reduced respiratory muscle function leading to task failure in healthy adults. Accordingly, the purpose of this study was to: (1) determine the feasibility of spatially resolved NIRS to measure tissue oxygenation of SCM, parasternal (PS) and scalene (SA) during incremental ITL in healthy adults; and (2) examine the acute effect of normobaric hypoxia (FIO2= 15%) on respiratory muscle oxygenation during incremental ITL. We hypothesized that in healthy people: (1) NIRS would be a feasible non-invasive tool to quantify inspiratory muscle tissue oxygenation during incremental loading under normoxic and hypoxic conditions, (2) for SCM, HHb would increase progressively and TSI would decrease prior to task failure during ITL under both conditions, and these changes would be accentuated during hypoxic ITL. 2.2 Methods Healthy participants were recruited from the general population in Vancouver. Inclusion criteria were: adults aged 20 years or older, non-smokers and no history of heart or lung 39  disease. Exclusion criteria were: elite athletes, skin hypersensitivity, chronic illnesses that would affect blood flow or gas exchange and adipose tissue thickness greater than 10 mm over the target muscles. A detailed verbal explanation of the nature of the study and written, informed consent was obtained from participants. All experimental procedures and protocols were approved by the University of British Columbia Clinical Research Ethics Boards and Vancouver Coastal Health Research Institute.  2.2.1 Experimental protocol The study was a single-blind cross-over design with repeated measures. Subjects were randomly assigned to perform ITL during normoxia or hypoxia. Participants attended a screening visit and two testing visits. During the screening visit, participants’ anthropometric data were evaluated (height, mass, age). Exclusion criteria were screened for including previous medical history, and completion of the American Heart Association and American College of Sports Medicine Health Fitness Facility Pre-Participation Screening Questionnaire (Balady et al., 1998). To confirm the suitability for NIRS monitoring, subcutaneous adipose thickness over the target muscles was measured using skinfold calipers (JAMAR, Patterson Medical Holdings Inc, IL, US). Standardized procedures for spirometry and maximal inspiratory pressures (MIP) were performed (Miller et al., 2005). Participants were familiarized with inspiratory threshold loading by using a threshold trainer (Threshold®IMT, Vacumed, Respironics Inc, U.S). The participants were asked to refrain from strenuous exercise for at least 48 hours and from caffeine intake for 12 hours prior to the ITL tests. NIRS optodes were positioned with subjects in sitting position with feet flat on floor, knees flexed at 90 degrees and forearms rested on a table at waist level. The head and neck were supported in a neutral position by 40  a head chin rest. Subjects breathed through the assigned gas mixture (in a blinded fashion) for four minutes followed by the performance of a minimum of three MIP maneuvers. This was followed by two minutes of tidal ventilation while breathing the assigned gas mixture and then the first ITL test was performed until task failure. MIP measures were immediately repeated and again every 10 minutes until 30 minutes of recovery.  At least four days later, subjects performed the identical protocol while breathing the other gas mixture.  Heart rate (HR) via 3-lead electrocardiogram (EKG), mean arterial pressure (MAP) and arterial oxygen saturation (SpO2) via finger probe pulse oximetry (Passport 2, Datascope Corp, Mahwah, NJ) were monitored throughout the protocol. The 10-point Borg scale (Borg, 1982) was utilized to determine dyspnea intensity prior to the start of ITL, at task failure and at 30 min of recovery.  2.2.2 Near-infrared spectroscopy  To determine the effect of increasing respiratory load as well as exposure to the hypoxic gas mixture on O2Hb, HHb, tHb, and TSI of the muscles of interest, commercially available NIRS devices (Portamon, Portalite and Oxymon M III, Artinis Medical Systems, BV, Netherland) were utilized. These devices incorporate the modified Beer-Lambert law (Wahr, Tremper, Samra, & Delpy, 1996). The Portamon and Portalite devices incorporate spatially resolved spectroscopy which provide an additional measure of TSI. Oxymon consists of optical fibers connected to optode holders, each of which holds transmitter and a receiver optodes placed 35 mm apart. Portamon and Portalite are portable, wireless NIRS devices that have three transmitters and one receiver with interoptode distances of 30, 35, and 40 millimeters (mm). The wavelengths of the infrared light range from 760 to 850 nanometer (nm). There is a slight difference between Portamon and Portalite. Portamon 41  weighs 84 grams and has dimensions of (83 x 52 x 20) mm whereas Portalite weighs 88 grams and has dimensions of (84 x 54 x 20 mm). Another unique feature of Portalite is that it has smaller optodes holder (58 x 28 x 6 mm) which is connected to the main device with a 1.3 meter wire.  NIRS devices were cleaned by using an alcohol swab before and after each experiment. The skin areas were cleaned with an alcohol swab before mounting the NIRS devices. The Oxymon probe was placed over the left SA, lateral to the SCM and just superior to the supraclavicular fossa. One Portalite and two Portamon devices were positioned over the left SCM, left PS  and left TA, respectively. The placement of the NIRS devices were identified by the anatomical landmarks: (1) tibialis anterior placed at the upper half of an imaginary line between the tibial tuberosity and intermalleolar line; (2) the sternal head of SCM: at the middle third of the muscle belly between the mastoid process and sternal notch; (3) anterior SA: just above the clavicle in the hollow triangle; and (4) parasternal intercostal at the second interspace about two cm lateral from the sternal edge. Stretchy adhesive tape (Hypafix®, BSN Medical, Hamburg, Germany) was used to secure all four devices and when possible, double stick discs (3M health care, St. Paul, Canada) were applied to maximize adherence.  Portalite and Portamon NIRS data were transmitted wirelessly to a laptop while Oxymon NIRS data was transmitted from the main unit to the computer via a USB cable. Data were sampled at 10 Hz and saved on a laptop for further off-line analysis using Oxysoft software (Oxysoft, Artinis Medical Systems, BV, Netherland). Of important to note that different NIRS devices were used because of the suitability of device size to provide measures 42     Fig.2.1 Inspiratory threshold loading device 41 cm during ITL. Nevertheless, all devices were manufactured by the same company (Artinis), used the same software (Oxysoft) and the same algorithms. 2.2.3 Inspiratory threshold loading (ITL)  An open circuit breathing system was utilized to administer the normoxic or hypoxic gas mixtures, from cylinders of medical grade gas with an FIO2 of 20.9 % or 15% balanced with nitrogen, respectively. Gas flowed through a tube from the cylinder to a non-diffusing gas reservoir bag (30-liter Hans Rudolph, Kansas City, MO, USA) and then via wide bore tubing (27 mm) to the mixing chamber of the threshold loading device. The inspiratory threshold loading device consists of an inspiratory mixing chamber (27 cm length and 43 mm diameter). At the top of the chamber, a stopper was inserted. At 13.5 cm from the top, the weighted plunger rested on a rubber “O” ring and the distal end was covered with a laboratory film (Parafilm, American national can, Greenwich, CT, USA). A “J” shaped metal bar extended 41 cm vertically from top to bottom. This has an important function to vertically displace the plunger and to bear the weights at the distal end (Figure 2.1).      43  The ITL test began by loading the plunger with a 100 g weight. The weighted plunger imposes a threshold load during the inspiratory phase of the ventilatory cycle, with no load present during the expiratory phase. The plunger is lifted when a sufficient inspiratory pressure overcomes the applied weight. A subsequent load of 50 g was added every two minutes until task failure. Task failure was defined as the point when participants could no longer generate sufficient inspiratory pressure to raise the plunger on two consecutive attempted breaths. The partial pressure of end-tidal carbon dioxide (PETCO2), was maintained above 33 mmHg by adding supplemental CO2 of 8.07% to the circuit and below 45 mmHg by coaching subjects to breathe more deeply. The respiratory cycle was standardized to a breathing frequency of 10 breaths/min with a 33% duty cycle. Participants were guided to inspire for two seconds and expire for four seconds by listening to an auditory signal. Reproducible MIP measures were performed at residual volume and recorded immediately after the ITL completion and every 10 minutes thereafter. During ITL, ventilatory parameters including tidal volume (VT), inspiratory flow, inspiratory mouth pressure, PETCO2, and minute ventilation (VE) were recorded breath by breath at 200 Hz and converted to digital signals (PowerLab 16/30, ADInstruments, Colorado Springs, CO). Inspiratory airflow was recorded using a pneumotachograph (3813, Hans Rudolph, Kansas City, MO, USA). The pneumotachograph was connected between the threshold loading device and the inspiratory port of the two-way non-rebreathing valve (1400, Hans Rudolph, Kansas City, MO, USA). Mouth pressure was measured relative to atmospheric pressure from a side port of a stopcock on the mouthpiece, which was connected to a differential pressure transducer with range +250 mmHg (MP45, Validyne Corp, Northridge, CA, USA). The signals from the differential 44  pressure transducers were amplified via a carrier demodulator (CD 15, Validyne Corp, Northridge, CA, USA). An infrared CO2 sensor (Model 17630, VacuMed, Ventura, CA, USA) was also connected to another port of the stopcock to measure PETCO2. Before each experiment, the pneumotachograph was calibrated with a 3-liter syringe (5530, Hans Rudolph, Kansas City, MO, USA) according to the manufacturer’s specifications. The CO2 analyzer and pressure transducer were calibrated using a gas of known CO2 concentration (8.07%) and differential pressure manometer (HD750, Extech Instruments, USA), respectively. In addition, temperature, barometric pressure and humidity were logged and utilized to correct volume and flow measures.  2.2.4 Statistical analysis Statistical analysis was performed with Statistical Package for Social Science (version 22.0, SPSS Inc, Chicago, IL). A Shapiro-Wilk test was conducted to evaluate data distribution and categorize it as parametric or non-parametric. To compare cardio-respiratory response to normoxic and hypoxic ITL at baseline and task failure, Friedman’s test was conducted followed by the Wilcoxon Signed-Rank test if applicable. In order to analyze the change in NIRS variables, the duration of the ITL test was divided into five quintiles (0-20%, 20-40%, 40-60%, 60-80%, and 80% to task failure). Based on the gas mixture, the changes in NIRS variables from baseline to each quintile of ITL were computed in unit of micromole (µm). Four separate linear mixed effect models were carried out on each of the four dependent measures, O2Hb, HHb, tHb, and TSI, using gas mixture, muscle, time, and their interactions as fixed effects and subjects as the random effect. For an overall change in NIRS variables at task failure, four linear mixed models were conducted where time was not a factor. Bonferroni test was used as a post hoc test to 45  compare means (i.e. the different time-points, gas mixture, muscle and their interaction). A p value of <0.05 was considered statistically significant. Data are expressed in mean +SD unless otherwise stated. 2.3 Results Twenty healthy subjects (twelve men and eight women) with mean age 32 + 12 year and normal spirometry participated in the study (Table 2.1).  Table 2.1 Anthropometric and spirometric data (n=20) Measure Mean + SD Age (y) 32 + 12 Height (cm) 171 + 11 Mass (kg) 67.9 + 14.9 BMI (kg.m-2) 23.1 + 3.8 Mean adipose tissue thickness at optode sites (mm) 1.8+ 1.3  FVC (L) 4.1 + 1.3 FVC pred (%) 93.9+ 15.4 FEV1 (L) 3.7 + 1.0 FEV1 pred (%) 88.7 + 23.6 FEV1/FVC 0.86 + 0.12 FEV1/FVC pred (%) 100.5 +7.0 BMI, body mass index; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 sec Compared to baseline, ITL at task failure significantly increased peak mouth pressure (PmPeak)7.9 and 8.9 fold and PETCO2 increased by 5.1 + 6 and 4.4 + 4.8 mmHg during normoxia and hypoxia, respectively. Other ventilatory parameters did not change during 46  both normoxic and hypoxic ITL (Table 2.2). SpO2 decreased during hypoxic ITL from baseline to task failure and the values during hypoxic ITL were significantly lower than that shown during normoxic ITL (Table 2.2).  Table 2.2 Effects of normoxic and hypoxic ITL on performance, ventilatory and cardiac parameters at baseline and task failure  Normoxic ITL Hypoxic ITL ITL Length (min) 15.4 +  6.1 14.7 +  5.5 Max.Load (gm) 451.3 + 160.3 440.0 + 149.2  Baseline Task failure Baseline Task failure PmPeak (cmH2O) 10.4+ 3.1 82.8+ 28.5٭ 11.9 +3.4 81.5+27.0٭ VT (L) 1.4+0.5 1.3+0.5 1.5+0.6 1.3+0.6 VE (L/min) 13.0+ 4.5 11.4+4.6 12.7+5.5 10.9+4.3 Flow (L/s) 0.2+ 0.1 0.2+0.1 0.2+0.1 0.2+0.1 PETCO2 (mmHg) 34.1+3.0 39.2+5.2 ٭ 35.6+3.0 40.0 +3.8٭ SpO2 (%) 99+1 98+2 97+2† 95+3٭† Heart rate (bpm)                     78+8 87+11٭ 79+8 86+9٭ MAP (mmHg) 97+12 103+13٭ 98+16 104+16٭ Dyspnea 0 7.3 + 1.7 ٭ 0 7.0 + 2.1٭ VT, tidal volume; VE, minute ventilation; Flow, inspiratory flow; PmPeak, peak mouth pressure; PETCO2, partial pressure of end-tidal CO2; SpO2, arterial oxygen saturation via pulse oximetry; MAP, mean arterial pressure.  ٭ indicates significant difference from baseline and † indicates significant difference than normoxic values at p<0.05 Figure 2.2 shows the change in O2Hb, HHb, tHb and TSI from baseline to task failure for each muscle during normoxic and hypoxic ITL. The increase in O2Hb differed significantly between muscles (p = 0.01). Pairwise comparisons showed that O2Hb of  PS increased more so than O2Hb of SA and TA (7.5 + 1.2 vs 2.7 + 2.0 and 1.6 + 0.6 µm, respectively; p < 0.03). The gas mixture markedly affected HHb (p = 0.02); overall, HHb value during 47  Fig.2.2 Change in NIRS variables of the four muscles from baseline to task failure. Solid bars represent the normoxic data whereas the hatched bars represent the hypoxic data. Data are reported in mean + SE. * Indicates difference between muscles and ǂ indicates interaction between gas mixture and muscle (P < 0.05). The TSI of SA was not measured because the NIRS device (Oxymon) does not provide that data hypoxic ITL was significantly greater than during normoxic ITL.  Moreover, the HHb differed among muscles p < 0.001; in contrast to the decrease in HHb in TA, HHb increased in SA, SCM, and PS (-3.9 + 0.7 vs 3.0 +1.2, 4.9 +1.0 and 0.4 + 0.5 µm). In addition, SCM had a higher HHb than PS HHb, p < 0.001. The tHb differed among muscles, p < 0.001; a decrease in tHb for TA was observed, whereas tHb for SA, SCM and PS increased (-2.2 + 0.9 vs 5.8 +2.9, 9.5 + 1.2, and 8.1 + 1.2 µm); p <0.01. TSI differed among muscles (p < 0.01).  Pairwise comparisons revealed that SCM showed a significant reduction in TSI compared to the increase in TSI for PS and TA (-2.2 + 0.8 vs 3.5 + 0.9 and 3.1+ 0.6%; p < 0.01). Of note, hypoxic ITL induced a significant decrease in TSI levels in the SCM than normoxic ITL (-3.5 + 1.3 vs -0.9 + 0.7%; p = 0.04).          SA         SCM        PS            TA                      SA          SCM        PS            TA -6.0-∆ TSI (%)٭ ٭‡-6.0-∆ tHb (µm)٭ ٭٭-6.0-∆ HHb (µm)٭ ٭ ٭٭-6.0-∆ O2Hb (µm)٭٭48  Figure 2.3 shows changes in HHb and TSI for each muscle at each quintile of ITL during normoxia and hypoxia. HHb changed significantly over time in all muscles except PS (p = 0.02). Pairwise comparisons revealed that SA HHb significantly increased at 80% and task failure compared to 20% (p < 0.03), whereas SCM HHb was higher at 40, 60, 80% and task failure relative to 20% (p < 0.02). TA HHb decreased at 80% and task failure compared to 20%, p < 0.01. There was also a significant effect of gas mixture indicating that the overall mean of HHb for hypoxia were larger than during normoxia (1.0 + 0.2 vs. 0.1 + 0.2 µm; p < 0.001). Furthermore, there was a significant muscle × gas mixture interaction. Particularly, the increase in SCM HHb was significantly greater during hypoxia than normoxia (3.4 + 0.6 vs 1.4 + 0.4 µm; p < 0.00). Analysis of TSI showed a significant interaction of muscle × time, p < .001, indicated that SCM TSI significantly decreased at 80% and task failure compared to 20%, p < 0.02 while PS TSI increased at task failure compared to 20%. The decreases in SCM TSI was greater during hypoxic ITL.   -6-4-202468Baseline 20% 40% 60% 80% TaskFailureΔTSI (%)% of ITL duration-6-4-202468Baseline 20% 40% 60% 80% TaskFailureΔTSI (%)% of ITL duration -6-4-202468Δ[HHb] (µM)Normoxia-6-4-202468Δ[HHb] (µM)Hypoxia SA  SCM  PS  TA 49  Fig.2.3 Change in HHb of all four muscles and in TSI for SCM, PS and TA during each quintile of ITL. The dashed line indicates a significant interaction between muscle and gas mixture. Open markers denote significant differences from the 20% of ITL duration  2.4 Discussion To the best of our knowledge, this is the first study to use spatially resolved NIRS technology to quantify inspiratory muscle oxygenation during acute hypoxic and normoxic incremental ITL in healthy men and women. A primary finding was that acute hypoxia accentuates deoxygenation of the accessory inspiratory muscle (SCM) at ITL task failure as indicated by a decrease in TSI. Also, the increase in HHb could imply the deoxygenation of  tissue and oxygen extraction as described in previous studies (De Blasi et al., 1994; Wang et al. (2006). Measures of SCM deoxygenation, HHb and TSI, precede task failure with a differential time course; SCM HHb increased during the early stages and progresses throughout ITL, whereas the SCM TSI decreased during the stage just before task failure. Of importance, the PS not only maintained its oxygenation level but demonstrated an increased in TSI. The SA appeared to show an intermediate response between the SCM and PS. Deoxygenation in these inspiratory muscles and their different time sequence may be useful clinical indicators of pending ventilatory failure in conditions that result from increased loading and hypoxic stimuli.  The differential time course of the HHb and TSI measures of SCM may indicate the increased recruitment and the mismatching between oxygen demand and delivery. In this study, SCM HHb significantly increased from 40% of ITL duration to task failure, which was accompanied by a maintenance of O2Hb and linear increase in tHb. Collectively, these changes are consistent with increased recruitment of the SCM.  In contrast, a significant 50  decrease in SCM TSI was heralded later, at 80% and at task failure, which likely reflected when oxygen demand exceeded delivery. This postulate is consistent with the observation by Wang et al. (2006) who demonstrated that when oxygen consumption reached the lactic threshold, TSI dropped in synchrony with the increase of anaerobic metabolism.  Worthy of note, the combination of ITL and hypoxia augmented the decrease in SCM TSI 3.9 fold, whereas HHb increased 1.7 fold compared to normoxic ITL. This distinctive accentuation in TSI during hypoxic ITL was only demonstrated in SCM and not in PS. This may be due to the lower reserve capacity of SCM during ventilatory loading ascribed by its mechanical disadvantage and limited vasculature and oxidative capacity to increase oxygen delivery. This anatomical disadvantage may account for why SCM, as an accessory inspiratory muscle, is not recruited during quiet breathing but rather is active at higher levels of ventilation (Campbell, 1955; Hudson et al., 2007; Roussos, 1985). The mechanical disadvantage will result in less ventilation for a given recruitment of muscle fibers. The muscle fiber composition and associated capillarization could also contribute to a relative deoxygenation because of limited oxidative capacity. In young male cadavers, the muscle fiber type composition of SCM has been reported to be 61 to 65% type 2 fibres (Cvetko, Karen, & Eržen, 2012; M.A Johnson, Polgar, Weightman, & Appleton, 1973) compared to 64% type 1 fibers in internal intercostal muscle (Mizuno & Secher, 1989). To note, muscle fiber composition could differ among sexes, though this data is not presently available in the literature. In general, the greater muscular work and limited oxidative capacity of the SCM may explain why TSI decreased in this inspiratory muscle while it increased in  PS. 51  Our finding of increased SCM HHb is consistent with other studies of ventilatory loading in healthy humans. The pattern of SCM HHb increase during normoxic ITL is similar to those findings reported in healthy men (Katayama et al., 2015; Shadgan et al., 2011) during ITL and voluntary hyperpnea. Moreover, the increase in O2Hb of SCM in our study is similar to that reported by Shadgan et al. (2011). In contrast, SCM showed an early deoxygenation (decrease in O2Hb, increase in HHb and no change in tHb) that was noted during the first 20% of total ITL duration in moderate-to-severe COPD patients who underwent incremental ITL albeit at lower loads (Reid et al., in press). It would appear that because of the complex pathophysiology of COPD, the SCM O2Hb of COPD patients decreased during normoxic ITL, whereas in healthy people, SCM O2Hb is maintained even during hypoxic ITL. Of interest, the significant  decrease in TSI during hypoxic ITL is in accordance with a recent study that reported a greater SCM deoxygenation, decrease in TSI, during hypoxic isocapnic hyperpnea for ten minutes compared to the normoxic protocol (Katayama et al., 2015).  Our data differed from the study that utilized isocapnic hyperpnea during hypoxia (Katayama et al., 2015) that reported a greater increase in HHb and decrease in TSI of SCM. The larger changes reported in the study by Katayama et al. (2015) may be attributed to the greater magnitude of hypoxia (FIO2 of 10-12% versus 15%), differences in sex distribution and differences in the ventilatory pattern of loading. Particularly, in the current study, SpO2 declined to 95% at task failure compared to an SpO2 of 80% in the study by Katayama et al. (2015). Also, female participants were involved in our study but not in the investigation by Katayama et al. (2015). Moreover, ITL is characterized by lower velocity and higher loading relative to hyperpnea protocols that require high-velocity contractions 52  with low resistive loads. Thus, differences in participants, hypoxic stress and loading pattern may have influenced the magnitude of change in muscle oxygenation. Nonetheless, SCM was demonstrated to be vulnerable to deoxygenation in both studies. Worthy of consideration, in addition to deoxygenation of respiratory muscle, the increase in PETCO2 during the last stage of ITL could have played a role in task failure in our study. It has been suggested that during inspiratory resistive loading, the accumulation of CO2 is associated with increased dyspnea, which together may contribute to task failure (Gorman, McKenzie, & Gandevia, 1999; McKenzie, Allen, Butler, & Gandevia, 1997; Rohrbach et al., 2003).     SA and PS are primary inspiratory muscles that have been reported to be recruited at equivalent rates and order during tidal breathing (De Troyer & Estenne, 1984; Saboisky et al., 2007) However, our findings show distinct feature of these two muscles at task failure. PS O2Hb show the highest increase that differed from smaller increases of SA O2Hb. A second difference was that the complementary measure, HHb, did not change throughout both hypoxic and normoxic ITL in PS, whereas it increases significantly at 80% and task failure during both ITL tests in SA. These observations are consistent with EMG data that showed the SA to be less resistant to fatigue than the PS during maximal cycling exercise (Segizbaeva et al., 2013). Taken together, it would appear that a mismatch between oxygen supply and demand that occurs in SA is not apparent in PS during hypoxic and normoxic ITL. This postulate is supported by data from animal models that show the PS to have a higher perfusion during ventilatory loading even compared to the diaphragm (Hussain, 1996), whereas the scalene increased blood flow to 33% of that shown in the diaphragm during resistive loading (Robertson et al., 1977). If similar proportions of increased blood 53  flow occur in humans, oxygen delivery to PS was sufficient to prevent this muscle from deoxygenating even at high levels of ventilatory work, whereas the SA appeared to show signs of an imbalance between oxygen demand and supply.  It is generally accepted that during exercise, oxygen supply to the active muscle is promoted to match the demand and this results in an increased blood volume (tHb) to the exercising muscle (Wang et al., 2006). In the case of respiratory muscle exercise at high level of ventilation, blood flow is thought to be redistributed from inactive muscle to respiratory muscles (Sheel et al., 2001); this phenomenon has been termed the respiratory muscle metaboreflex. We found that during incremental ITL, tHb in all inspiratory muscles gradually increased in order to meet the demand, whereas TA tHb decreased similar to the pattern shown in quiescent muscle, vastus lateralis,  by Shadgan et al. (2011). This finding is consistent with the metaboreflex concept though a surrogate measure of blood volume was assessed and no measure of the sympathetic output was evaluated. Perhaps, it is of no surprise that tHb of the inspiratory muscles did not differ between hypoxic than normoxic ITL because previous studies have suggested that blood volume to respiratory muscles is not affected by hypoxia during breathing exercise or even during whole body exercise (De Bisschop et al., 2014; Katayama et al., 2015).  Worthy of note, it was surprising that the TSI increased in TA whereas the tHb decreased at task failure. However, one possible explanation, in part, would be the effect of ITL on the shift in blood volume from the venous capacitance vessels. It is generally accepted that veins normally contain 65 to 75% of blood volume at rest (Krishnan, Taneja, Gewitz, Young & Stewart, 2009). This observation, taken together with the finding that during inspiratory muscle loading, sympathetic nerve activity of resting limb muscle increases 54  causing an increase  in limb vascular resistance (Sheel et al., 2001; St Croix et al., 2000). Thus, we hypothesised that the increase in TA TSI occurred because of the venous vasoconstriction  and thus the TSI represented a larger proportion of arteriole and less of a venues contribution. To our knowledge, the observation between TSI and tHb of resting limb muscle has not been reported in any of the previous studies. Therefore, further study is needed to closely investigate the relationship between the increase of TSI and decrease of tHb in a control muscle during ITL.    Regarding the cardiovascular response to ITL, increases in heart rate and mean blood pressure were shown at task failure compared to baseline. However, there was no effect of hypoxia compared to normoxia on heart rate and mean blood pressure at baseline and during ITL. The increase in heart rate and mean blood pressure could be attributed to the increase in sympathetic nervous system discharge and a decrease in parasympathetic discharge associated with increased exertion (Houssiere et al., 2005; Yamamoto, Hoshikawa, & Miyashita, 1996). The FIO2 of 15% compared to normoxia was likely not sufficient to show a differential cardiovascular response during ITL, which is consistent with a previous study that examined the effect of acute exposure to mild-to-moderate normobaric hypoxia (simulated altitude range from 500 to 2500 m) on the cardiac autonomic nervous system adjustment during mild and moderate exercise (Yamamoto, Hoshikawa, & Miyashita, 1996). In contrast, more severe hypoxia as demonstrated by an FIO2 < 12% resulted in a remarkable rise in heart rate compared with breathing ambient air at baseline (Zattara-Hartmann & Jammes, 1996) and during exercise (Houssiere et al., 2005; Katayama et al., 2015).  55  2.4.1 Study limitations Limitations of this study include the small sample size, placement of NIRS optodes and shortcomings of NIRS measures. A sample size of twenty individuals may not represent potential variations attributable to sex and age that might become apparent in a larger sample. Because skeletal muscle has a heterogeneous oxygenated composition (Miura, McCully, Nioka, & Chance, 2004), the initial placement of NIRS probes were marked using an indelible marker to ensure identical placement during the second visit. A third issue might be how muscle movement affects NIRS monitoring. NIRS measures provide estimates based on the assumptions, that tHb is indicative of blood volume beneath the probe. Changes in muscle architecture beneath the probe during muscle contraction even if quasi-isometric may contribute to variations of this measure not solely attributable to blood volume but rather to movement of tissue beneath the optode. Optode movement was minimized by adherence with two types of tape fixation and neck movement was constrained by resting the chin on a head-chin support. One last limitation is that TSI value was not available for SA because of the Oxymon device does not provide this measure. Unfortunately, the short necks of female participants precluded the use of alternative spatially resolved NIRS device on SA because of poor adherence during loaded breathing.  2.4.2 Conclusions This study demonstrated the feasibility of using NIRS to measure respiratory muscle oxygenation during hypoxic inspiratory loading in healthy adults and is the first to report the oxygenation pattern of SA during hypoxic loaded breathing. The main finding of this study was that SCM TSI significantly decreased at task failure of ITL, and this decline was 56  accentuated by hypoxia. Increasing ventilatory demands of PS appeared to be met by proportionally increased O2Hb and tHb. In regard to the change in HHb, it remained stable throughout the test in PS, whereas it increased in SA and SCM. However, SCM showed earlier increase in HHb at 40% of ITL compared with late increase in SA HHb at 80% of ITL. The differential response of the SCM, SA and PS may be attributed to their relative mechanical advantage, where SCM is at the greatest disadvantage and secondly, to the ability to increase blood flow distribution during exertion, which appears greatest in the PS.           57  Chapter Three: Inspiratory muscle myoelectric manifestations and task failure during normoxic and hypoxic inspiratory loading: A Pilot study 3.1 Introduction  The diaphragm is the primary inspiratory muscle although other neck and chest wall muscles like the scalene (SA), sternocleidomastoid (SCM), intercostals and pectoralis work in synchrony to generate adequate intrathoracic pressures during high ventilatory loads (De Troyer et al., 1994; Similowski et al., 1998). In a variety of respiratory diseases, inspiratory muscles are prone to fatigue. Respiratory muscle fatigue can in turn contribute to ventilatory failure, a life-threatening condition; therefore evaluation of respiratory muscle fatigue may be an essential clinical tool to early diagnose the imminent ventilatory failure.  This could enable resting the fatigued muscles in order to prevent exertion-induced muscle injury. However, the challenge of mechanically ventilating patients is that 26 to 42% of these patients fail to wean (Boles et al., 2007; Peñuelas et al., 2011). Multiple pathophysiological components may contribute to weaning failure. Of these, the increase in respiratory muscle fatigue, work of breathing, airway resistance, hypoxemia and  hypercapnia at the onset of the weaning protocol are all potential factors (Jubran & Tobin, 1997; Tobin, Laghi, & Brochard, 2009;Vassilakopoulos et al., 1996; Zakynthinos et al., 2005).  Surface electromyography (sEMG) has been used to examine respiratory muscle recruitment and fatigue in healthy individuals and patients various disorders. Several studies have evaluated inspiratory muscle recruitment patterns in patients on mechanical ventilation and during weaning. Brochard and colleagues (1989) suggested that monitoring SCM activity provides valuable insight into the optimal mechanical ventilation settings 58  that may limit diaphragm fatigue. In the same vein, other investigators correlated the increase in SA activity with dyspnea perception in subjects on pressure support ventilation (Chiti et al., 2008; Schmidt et al., 2013).  During spontaneous breathing trials in a weaning protocol, researchers found greater SCM activity in patients who failed weaning than those that succeeded in weaning (Parthasarathy et al., 2007). Nevertheless, many investigators have reported difficulty in measuring the respiratory muscle EMG activity of SA and SCM simultaneously mainly because of the high cross-talk probability (Chiti et al., 2008; De Troyer et al., 1994; Hug et al., 2006). Over the last 20 years, high density surface EMG using linear arrarys has been validated to detect and to improve the quality of myoelectrical activity recordings from trunk and peripheral muscles in healthy and diseased populations (Rojas-Martínez et al., 2012; Merletti et al., 2003; Zwarts et al., 2000). This technique was shown to limit the influence of anatomical factors, such as the presence of an innervation zone under the electrodes, on EMG estimates (Smith et al., 2015); in addition, fatigue-related decreases in median frequency were more prominent when assessed over many electrodes than in simulated bipolar detection (Gallina, Merletti, & Vieira, 2011). It has been postulated that cross-talk from adjacent muscles could be minimized during voluntary contraction by using array EMG (De Luca et al., 2012). Interestingly, the EMG manifestation of fatigue was successfully described in the SCM and SA when they were recruited as neck flexors (Falla, Rainoldi, Merletti, & Jull, 2003).  Whether arrays of electrodes can identify changes in EMG signals indicative of fatigue in the SCM and SA during increased ventilatory loading is currently unknown. 59  To mimic a condition of increased ventilatory efforts in the presence of hypoxemia, numerous investigators have examined the effect of hypoxia on respiratory muscle fatigue during whole body exercise. Studies have shown greater diaphragm fatigue development during hypoxic compared with normoxic exercise (Babcock et al., 1995; Perlovitch et al., 2007; Verges et al., 2010; Vogiatzis et al., 2007). Despite the considerable advancement in hypoxic exercise research in humans, there are limited data on the contribution of the inspiratory neck muscles during increased inspiratory loading in hypoxia. The only published study that compared the magnitude of accessory inspiratory muscle activity during hypoxic hyperpnoea showed a significant hypoxic effect on augmentation of SCM recruitment (Katayama et al., 2015). Thus, the primary aim of this study was to compare the EMG activation and signs of fatigue from SA and SCM during normoxic incremental inspiratory threshold loading (Norm-ITL) and hypoxic (HYP-ITL, FIO2=0.15) in healthy adults. The secondary aim was to investigate the effect of hypoxia on the endurance, the highest load that could be achieved. We hypothesized that the increase in inspiratory loads would result in increased SA and SCM activation and secondly, that HYP-ITL would accentuate EMG activity and fatigue, which, in turn, would exaggerate dyspnea perception and reduced endurance. 3.2 Methods 3.2.1 Participants Twenty healthy adults aged between 20 to 65 years participated. Elite athletes, active smokers, people with hypersensitive skin and individuals who were diagnosed with respiratory diseases or chronic illnesses were excluded from the study. Due to some technical problems, thirteen (nine male: four female) out of the twenty subjects were 60  included in the analysis. All subjects provided written informed consent prior to participating. The study was approved by the University of British Columbia Ethics Review Board and Vancouver Coastal Health Research Institute. 3.2.2 Experimental procedure This was a single-blind cross-over, repeated measures design. Subjects attended a preliminary visit and two testing visits (Figure 3.1).        During the preliminary visit, participant’s anthropometric data were obtained followed by routine spirometry as per established guidelines (Miller et al., 2005). Subjects were also familiarized with the ITL protocol using a threshold trainer device (Threshold®IMT, Vacumed, Respironics Inc, U.S) and with maximum inspiratory mouth pressure (MIP) maneuvers performed at residual lung volume (Black & Hyatt, 1969). For the next two testing visits, subjects were asked to refrain from strenuous exercise and from caffeine intake for 48 hours and 12 hours respectively, prior to the ITL tests. During testing visits, subjects were comfortably seated in an upright position, the head was supported in a neutral Fig.3.1 Schematic representation of the experimental design of the study Screening visit: Obtained:  Written consent Anthropometric data Spirometry Familiarization  ITL protocol  MIP Group          A Normoxic ITL visit Washout period > 3 days Hypoxic ITL visit GroupB Normoxic ITL visit Hypoxic ITL visit 61          Fig.3.2 An outline of  ITL protocol position and EMG electrodes were fixed to the skin. Subjects breathed a randomly assigned gas mixture of 0.21 or 0.15 FIO2 through the mouthpiece for four minutes. Three reproducible MIP maneuvers were then performed which was followed by two minutes of unloaded breathing. Then, subjects performed an isocapnic incremental ITL test. To maintain isocapnic condition, CO2 supplement was titrated into the inspiratory circuit, as required. Dyspnea was quantified before ITL, at task failure then 30 minutes later using the modified 0-10 point Borg scale (Borg, 1982). MIP was recorded again immediately after the ITL cessation and 10 minutes thereafter. Throughout the test, ventilatory parameters were measured continually. Mean arterial pressure (MAP), heart rate (HR) and arterial oxygen saturation (SpO2) were monitored. An outline of  ITL protocol is illustrated in Figure 3.2.           Before loading:  4 min breathing the assigned gas  MIP maneuvers  Recording MIP  Recording EMG from SA and SCM  2 min unloaded breathing controlled duty cycle   Dyspnea rating  Recording SpO2, HR, MAP   Recording ventilatory parameters Incremental inspiratory threshold loading:  ITL began by adding 100 grams of weight to ITL device  Every 2 min, load increased by 50 grams of weight  Recording ventilatory parameters  Recording EMG from SA and SCM  Recording SpO2, HR, MAP  Monitoring muscle oxygenation   Immediately after loading:  MIP maneuvers  Recording MIP  Recording EMG from SA and SCM 10 min of recovery   MIP maneuvers  Recording MIP  Recording EMG from SA and SCM 30 min of recovery   Dyspnea rating  Recording SpO2, HR, MAP  62  3.2.3 Spirometry A standardized procedure for spirometry measure was performed in accordance with the American Thoracic Society and European Respiratory Society recommendations using standard techniques (Miller et al., 2005). Forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and the FEV1/FVC ratio were obtained using a portable spirometer (Spirodoc, Medical International Research, Roma, Italy). The test was repeated a minimum of three times until <0.15 L differences was obtained between the readings.  3.2.4 Inspiratory threshold loading protocol A custom-built ITL device, as described previously by Shadgan et al. (2011), was used. ITL began by adding a 100-gram weight to the ITL device. The load was increased by 50 grams every two minutes until task failure, which was defined as the point when the subject could not generate sufficient inspiratory pressure to raise the plunger on two consecutive breaths. Subjects were cued by auditory signals to a standardized breathing frequency (fb) of 10 breaths/min with a 33% duty cycle (2 s inspiration / 4 s expiration). No instruction was given regarding breathing pattern (i.e. inspiratory muscle to be recruited, tidal volume and inspiratory flow). Figure 3.3 is an image of the ITL set-up with the data acquisition system and the non-diffusing gas reservoir bag. 63   Fig.3.3 ITL set-up; A: Breathing apparatus, B: Data acquisition, C: Non-diffusing gas reservoir bag 3.2.5 Respiratory muscle activity (EMG)  EMG signals were acquired with two electrode arrays (ELSCH 008, OT Bioelettronica, Torino, Italy) from the sternal head of SCM and anterior SA. The two electrode arrays, which consisted of eight electrodes (1 mm diameter with 5 mm interelectrode distance), were attached to the skin with adhesive foam (KITAD008, OT Bioelettronica, Torino, Italy) and filled with conductive cream (CC1, OT Bioelettronica, Torino, Italy). Skin preparation was performed in accordance with SENIAM recommendations (Hermens, Freriks, Disselhorst-Klug, & Rau, 2000). Identification of SCM was determined by palpating the muscle belly during submaximal neck flexion contractions where a reference line was identified from the inferior edge of mastoid process to the center of sternal notch. As suggested by Falla et al. (2002), the electrode array was placed on the lower half of the 64  muscle. For the anterior SA, the electrode array was placed in the posterior triangle of the neck at the level of the cricoid cartilage. Both arrays were placed along the approximate muscle fiber orientation.  Two reference electrodes (H59P, Kendall-LTP, Covidien, MA, USA) were placed on the lateral aspect of the right acromion and coracoid processes. To facilitate sufficient electrode-skin contact and to minimize the electrode-skin impedance, electrode arrays were secured in place using adhesive tape.  In addition, the array’s wires were fixed to reduce the risk of cables being pulled and to inhibit artifacts from limb movement (Hermens et al., 2000; Sbriccoli et al., 2009). The EMG signals were collected in monopolar modality using OT BioLab (OT Bioelettronica, Torino, Italy), amplified with a gain of 500 V/V, digitized at 2048 Hz and filtered (Butterworth, 4th order, 20-400 Hz). 3.2.6 Ventilatory parameters Subjects breathed through a mouthpiece that was connected to a two-way non-rebreathing valve (1400, Hans Rudolph, Kansas City, MO, USA). The valve was connected to a pneumotachograph (3813, Hans Rudolph, Kansas City, MO, USA) to measure inspiratory flow, which was subsequently used to determine fb, tidal volume (VT) and minute ventilation (VE). Also, a continuous measure of inspiratory mouth pressure (Pm) and partial pressure of end-tidal CO2 (PETCO2) were recorded  via (MP45, Validyne Corp, Northridge, CA, USA)  and (Model 17630, VacuMed, Ventura, CA, USA), respectively. Ventilatory parameter were sampled at 200 Hz, converted to digital signals (PowerLab 16/30, ADInstruments, Colorado Springs, CO), displayed on real-time using (LabChart, ADInstruments, Colorado Springs, CO) and stored for off-line analysis (Figure 3.4). Ventilatory parameters were averaged over the last 30s of baseline as well as the last 30s of each ITL quintile. Inspiratory muscle force was determined upon the product of the 65  integration of Pm and fb. Before each experiment, standard volume, pressure and gas calibration procedures were performed. MIP predicted values were determined according to the equation proposed by Evans & Whitelaw (2009) as a function of age and sex. The equation for a healthy female is 108 - ( 0.61* age) and for a healthy male is 120 - (0.4* age). Fig.3.4 Ventilatory parameters (mouth pressure, tidal volume, flow and peak mouth pressure) from a representative subject 66  3.2.7 EMG data processing Data were processed using Matrix Laboratory “MATLAB” (MATLAB, version 8.3.0., Natick, Massachusetts: The MathWorks Inc., 2014). To increase the detection volume along the muscle, single differentials were calculated from non-adjacent monopolar signals. Signals were filtered (Butterworth, 4th order, 20-400 Hz) and visually inspected; noisy channels were excluded from the analysis. For each array, the three consecutive differential channels with the largest action potentials were included in the analysis. This approach helped avoid the channels above the innervation zones. Innervation zones were identified as the traces resembling to phase reversal of two signals and a minimum in signal amplitude (Merletti et al., 2003). The ITL test was divided into five equal quintiles (20%, 40%, 60%, 80% and task failure). For each quintile, EMG amplitude was normalized to the EMG from the highest MIP and was calculated as the average root mean square value (RMS) of the last five inspirations of each quintile. The frequency content of the EMG signal was calculated for the highest MIP as the median spectral value calculated on non-overlapping epochs of 250 milliseconds (ms). Both amplitude and frequency estimates were averaged over the 3 channels included in the analysis for each array. An example of EMG data during ITL from one subject is given in Figure 3.5.       67   3.2.8 Statistical analysis Data are expressed in mean +SE. Statistical analysis was performed with SPSS (version 22.0, SPSS Inc, Chicago, IL). Data were examined for normality using the Shapiro-Wilk test. The Friedman test was conducted followed by the Wilcoxon signed rank test for nonparametric comparisons. Two-way repeated measures ANOVAs with the Bonferroni corrections were performed to examine the differences in HR, MAP and dyspnea. Also, two linear mixed effect models with the Bonferroni post-hoc test were carried out on EMG data, using gas mixtures, muscles, and their interactions as fixed effects and subjects as the random effect. Time was considered as a control variable.  B Fig.3.5 A:Raw EMG data from SA and SCM, B: selected channels and time window. Blue signals indicate the last five breaths of  the each interval.   0 100 200 300 400 500 600-1012345678SCM YE, ITL, MaxVal: 794.19Channels (number)Time (s)0 100 200 300 400 500 600-1012345678SCA YE, ITL, MaxVal: 1792.74Time (s)SCM SA Channel Channel 68  3.3. Results 3.3.1 Descriptive characteristics Participant characteristics are shown in Table 3.1. All participants had normal spirometry values. The maximum load was similar at task failure during Norm-ITL and HYP-ITL, 481 + 43 and 481 + 42 grams, respectively. Table 3.1 Anthropometric and spirometric data (n=13) Measure Mean + SE Age (y) 33 + 4 Height (cm) 171 + 3 Mass (kg) 67.5 + 3.1 BMI (kg.m-2) 23.0 + 1.0 FVC pred (%)a 90.0 + 3.9 FEV1 pred (%)a 97.9 + 5.3 FEV1/FVC pred (%)a 101.0 + 2.9 MIP (cmH2O) 122.7 + 9.8 MIP pred (%)b 100.1 + 3.9 BMI, body mass index; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 sec; MIP, maximal inspiratory pressure. a predicative values were calculated using the formula from Hankinson, Odencrantz and Fedan (1999). b predicative values were calculated using the formula from Evans and Whitelaw (2009) 3.3.2 Ventilatory parameters No differences were demonstrated for ventilatory parameters between Norm-ITL and HYP- ITL at all time-points except for the inspiratory force index. At the baseline the inspiratory force index was greater during HYP-ITL, was great than Norm-ITL (Table 3.2). PETCO2 was significantly higher at task failure compared to all previous time-points 69  during both tests (p<0.01). Not surprisingly, PmPeak increased continuously in line with the progression of ITL (p<0.02). The progressive increase in inspiratory force was significant from baseline to 80% of Norm-ITL. On the other hand, it leveled off at 60% during HYP-ITL. Table 3.2 Ventilatory parameters at baseline, 20, 40, 60, 80% and task failure of Norm-ITL and HYP-ITL. Parameters Gas Time   Baseline 20% ITL 40% ITL 60% ITL 80% ITL Task failure VT  (L) Norm 1.4 + 0.1 1.4 + 0.1 1.4 + 0.1 1.4 + 0.1 1.4 + 0.1 1.3 + 0.1   Hypo 1.6 + 0.2 1.7 + 0.1 1.7 + 0.3 1.6 + 0.2 1.4 + 0.2 1.3 + 0.2 VE (L/min) Norm 12.8+ 1.0 12.7+ 1.0 12.3+ 1.1 12.4+ 1.0 12.4+ 1.2 11.6+ 1.4 Hypo 13.7+ 1.7 15.1+ 2.9 15.4+ 2.7 14.3+ 2.2 11.9+ 1.6 11.1+ 1.3 PmPeak (cmH2O) Norm 10.3+ 1.0 36.9 +3.7 49.9+ 4.1 64.7+ 5.4 78.7+6.6 86.1+ 8.2 Hypo 12.7+ 1.0 41.9 +4.0 56.9+ 4.3 70.5+ 5.7 78.3+6.8 87.2+ 7.6 fb x ∫ Pm (cmH2O.s. min-1) Norm 168+19 680+74 998+94 1266+133 1563+124 1764+218٭  Hypo 222+16** 782+97 1181+113 1765+418 1753+230† 1772+145٭ PETCO2 (mmHg) Norm 34.1+ 0.9 33.5+ 0.8 34.1+ 0.9 34.9+ 1.3 36.4+ 1.3 39.6+ 1.5 Hypo 35.6+ 0.9 35.2 + 1.2 36.0 + 1.1 35.7 + 1.0 37.3+ 1.0 40.9 + 1.0 VT, tidal volume; VE, minute ventilation; PmPeak, peak mouth pressure; fb x ∫ Pm, inspiratory force index; PETCO2, partial pressure of end-tidal carbon dioxide. Bold numbers represent a significant difference from all previous measures. ٭ indicates difference from all time points except 80%.  † indicates difference from all time points except 60% and task failure. ** indicates difference from Norm-ITL. At p<0.05 70  3.3.3 SpO2, HR, MAP and dyspnea HR and MAP were not different during HYP-ITL compared to Norm-ITL (Figure 3.6). Moreover, HR and MAP increased significantly from baseline to task failure in both conditions (p< 0.04). However, SpO2 at task failure was lower in HYP-ITL than Norm-ITL (p=0.01). SpO2 remained stable during Norm-ITL, whereas during HYP-ITL, SpO2 was significantly decreased from baseline (97+0.5%) to task failure (94+0.8%) and increased at recovery (99+0.3%) (p=0.002). Figure 3.6 shows SpO2, HR and MAP at baseline, task failure and 30 minutes of recovery.  Dyspnea rose from zero at baseline to 7.5+1.8 and 7.3+1.9 Borg units in Norm-ITL and HYP-ITL, respectively (p<0.001). Dyspnea did not differed between the two ITL conditions.   Fig.3.6 Arterial oxygen saturation via pulse oximetry (SpO2), heart rate (HR), and mean arterial  pressure (MAP) at baseline, ITL task failure and recovery.  ٭  significant difference from baseline and recovery. † significant difference between Norm-ITL and HYP-ITL (P <0.05)  71  3.3.4 EMG  The MIP did not differ between gas conditions and did not change among different time-point: baseline, immediately after task failure and 10 minutes of recovery. The EMG median frequency of the SA and SCM obtained during the MIP did not change significantly. Also, hypoxia did not affect these measures (Figure 3.7).   During incremental ITL, the RMS of the EMG activity of SA and SCM showed a significant progressive increase with increasing workloads, in turn, increasing ventilatory efforts (p<0.001). Of note, the RMS of the SA and SCM increased more so during HYP-ITL than Norm-ITL (p<0.001). Pairwise comparisons between muscles revealed that SA had higher RMS than SCM (p<0.02). Time was positively correlated with RMS, Pearson’s (r) = 0.57, p < 0.001. Figure 3.8 shows the progressive increase in RMS of SCM and SA. 6080100120EMG median frequency (Hz)Baseline Task failure Recovery6080100120140Norm-ITL HYP-ITLMIP (cmH2O)Fig.3.7 Maximum inspiratory pressure (MIP) and associated EMG median frequency of SA and SCM during MIP maneuver at baseline, task failure, and at 10 min recovery.  Means +SE are shown 72       3.4 Discussion The current study evaluated, for the first time, the acute effect of breathing a hypoxic gas mixture (FIO2=0.15) on the EMG of SA and SCM during ITL. The results showed that the SA and SCM activation increased proportionally with increasing workloads. Moreover, this increase in muscle activation was accentuated when progressive inspiratory loading was imposed during moderate hypoxia (FIO2=0.15). In spite of increased muscle activation, no signs of muscle fatigue were detected, based on the EMG median frequency and MIP values during the MIP maneuver taken after either ITL protocol. The overall performance in term of endurance, dyspnea and ventilatory response were comparable in Norm-ITL and HYP-ITL.  SCM activity has been evaluated during different breathing patterns in healthy individuals and patients with respiratory disease. In healthy young adults, SCM does not appear to be recruited during tidal breathing, light incremental ITL that ends at a load of 40 cmH2O (Nobre et al., 2007) and during constant ITL equivalent to 15 to 30% of MIP (Chiti et al., Fig.3.8 Means+SE of RMS of SA and SCM at 20, 40, 60, 80% and task failure of ITL. Black bars indicate Norm-ITL, whereas the gray bars indicate HYP-ITL. ٭ indicates significant difference between Norm-ITL and HYP-ITL. At  p<0.05  01020304050607080SCM SCM SA SAEMG RMS (% MIP)* * 73  2008; De Andrade et al., 2005). On the other hand, it becomes active during greater incremental ITL (Shadgan et al., 2011) and isocapnic hyperpnea (Katayama et al., 2015). In addition, Katayama et al. (2015) observed a remarkable increase in SCM activity during hypoxic hyperpnea compared to normoxic hyperpnea. In the case of patients with chronic obstructive pulmonary disease (COPD), the SCM demonstrated greater recruitment when COPD patients performed constant ITL at 30% of MIP (De Andrade et al., 2005) and when they underwent a failed weaning trial (Parthasarathy et al., 2007). In this study, the SCM RMS EMG increased from 13.3+1.9% and 19.0+3.5% at 20% of ITL to 57.3+5.9% and 63.0+7.6% at task failure, during Norm-ITL and HYP-ITL, respectively. This result is consistent with those obtained by Shadgan et al. (2011) and Katayama et al. (2015) that the SCM is an accessory inspiratory muscle that is activated at high ventilatory work and that hypoxia accentuates its activation in healthy adults (Katayama et al., 2015).   Our results demonstrated greater EMG amplitude of the SA than SCM during ITL.  Because the EMG values were normalized to the maximum EMG value during MIP, this suggests a larger recruitment of SA than SCM during ITL. These data are consistent with two other findings.  First, the SA is an obligatory inspiratory muscle active during tidal breathing and at high ventilatory efforts (De Troyer & Estenne, 1984; Gandevia et al., 1996). Studies have shown that increasing ventilatory efforts during breathing exercise is associated with progressive increases in SA activity in healthy subjects and to a greater degree in COPD, even with modest efforts (Chiti et al., 2008; Duiverman et al., 2004, Duiverman et al., 2009). Second, based on the neuromechanical matching principle, SA has a greater mechanical advantage and lower activation threshold relative to the SCM (Hudson et al., 2007; A. Legrand et al., 2003). Although the SA has lower mass compared 74  to the SCM, the greater fractional changes in SA length was attributed to the greater mechanical advantage (A. Legrand et al., 2003). MIP has been frequently used as an index of inspiratory force decline and as an indirect index of inspiratory muscle fatigue. Studies that have utilized MIP as an index of fatigue have reported conflicting results; Hawkes et al. (2007) showed potentiation in MIP, whereas others indicated no change in MIP after inspiratory loading tests (Eastwood, Hillman, & Finucane, 1994; 2001; Gorman et al., 1999; Shadgan et al., 2011). This inconsistency may be explained, at least in part, by differences in study designs.  Another explanation is that MIP is an indicator of global inspiratory muscles strength where fatigue of individual inspiratory muscle can not be reflected by this measure (“ATS/ERS statement on respiratory muscle testing,” 2002; Clanton & Diaz, 1995; Mathur, Sheel, Road, & Reid, 2010).  Consistance with no change in MIP, the median EMG frequency did not provide evidence of peripheral muscle fatigue. The absence of peripheral muscle fatigue supports the postulate that inspiratory muscle fatigue is dependent on breathing frequency and duty cycle. Previous observations have shown, that breathing against a constant resistive load at a duty cycle of 33% does not induce diaphragm fatigue (St Croix et al., 2000; Sheel et al., 2001). Similarly, incremental ITL protocols at an equivalent duty cycle did not show inspiratory muscle fatigue (Shadgan et al., 2011). The long exhalation period and controlled breathing frequency may prevent fatigue development even during hypoxic ITL. Another factor that likely contributed to fatigue resistance is that the breathing pattern was not controlled, which could influence the recruitment of other inspiratory muscles and therefore, reduce the probability of muscle fatigue (Laghi et al., 2014). Despite the high 75  level of activation in the SA and SCM during HYP-ITL, peripheral fatigue was not detectable. Collectively, our findings suggest that task failure occurs because of other central factors rather than peripheral muscle fatigue.   Task failure has been described as a defensive mechanism, protecting inspiratory muscles against contractile fatigue and damage during exercise. Hence, several theories have attempted to explain the underlying contributing factors of task failure. One of which is that task failure may occur due to hypoventilation coincident with hypercapnia. Laghi and colleagues (2014) defined the hypoventilation reaction as an inhibitory reflex that occurs in order to limit further diaphragm recruitment and possible injury. A significant increase in PETCO2 in our study is in agreement with those who reported a correlation between hypercapnia and task failure (Gorman et al., 1999; Laghi et al., 2014; McKenzie et al., 1997).  In some studies, hypercapnia was associated with intolerable dyspnea that could also contribute to task failure (Gorman et al., 1999; Rohrbach et al., 2003). Moreover, many investigators correlated the intensity of dyspnea to the magnitude of SA and SCM activation (Chiti et al., 2008; Schmidt et al., 2013). Taken together, the results confirmed that hypoventilation and dyspnea are some of the potential factors that lead to task failure. Experimental evidence has demonstrated that hypoxia reduces endurance performance and maximal work rate during whole body exercise (Amann et al., 2006; Fulco et al., 1996; Goodall et al., 2012;  Taylor and Bronks, 1996; Woorons et al., 2005). In contrast, the effect of hypoxia on the endurance of loaded breathing is inconsistent. One study has suggested that hypoxia attenuates endurance time (Jardim et al., 1981), whereas another did not reveal a difference between hypoxic and normoxic endurance time (Ameredes & Clanton, 1989). The result from the present study did not support our hypothesis that 76  hypoxia would reduce the endurance. Based on the current evidence, a shorter endurance test can be result from either peripheral, central muscle fatigue or the combination of both factors. Our finding revealed lack of peripheral muscle fatigue during HYP-ITL and Norm-ITL. Also, the central factors, dyspnea and PETCO2, were not significantly differed during both tests. Hence, we postulated that our hypoxic stimulus was insufficient to elicit peripheral muscle fatigue or further central muscle fatigue. It is well known that muscle properties, type of muscle contraction and hypoxic stimulus properties have a dual role in determining the extent of muscle fatigue evoked by hypoxia (Perrey & Rupp, 2009).   3.4.1 Study limitations Limitations of this study include a small sample size that did not allow to incorporate time as fixed factor in the mixed model analysis. Thereby, the time when muscle activity was significantly increased was not determined. In addition, a subgroup analysis was done on thirteen subjects due to some technical problems, mainly poor quality of EMG signals. This could have been addressed if we had performed a preliminary analysis on the data and then had sufficent time to redo the tests and perform the analysis on the higher quality data. Also, sex differences were not determined. Another potential limitation is that, although SpO2 and PETCO2 were measured, blood gas analysis was not performed which would have provided more insight regarding the acidity of blood (pH level). Accordingly, drawing a relationship between SpO2 and PETCO2 may be limited for several reasons. Firstly, SpO2 and PETCO2 were measured with two different devices. Secondly, SpO2 was determined at fixed time intervals in contrast to the continuous measurement of PETCO2. Therefore, the average of PETCO2 measures during the last five breaths is not comparable to a single SpO2 evaluation. Indeed, this is not the first study that showed mismatching 77  between SpO2 and PETCO2 measure during a hypoxic test. Verges et al. (2010) reported that PETCO2 did not differ whereas SpO2 was significantly lower during 15 minute normoxic and hypoxic hyperpnea tests.Third, as previously reported, signal contamination can not be eliminated when SA and SCM EMG activities are investigated. A fourth concern is that EMG signals were not synchronized with the respiratory cycle. Therefore, the initiation of inspiration was determined according to EMG signals, not to inspiratory flow.  3.4.2 Conclusions In conclusion, the increase in EMG RMS of the SA was greater than the SCM possibly reflecting the matching between the neural drive and the mechanical advantage of the SA during ITL. Despite the significant increases in SA and SCM activation during hypoxic ITL, muscle fatigue was not observed after both ITL tests. Thus, we postulated that task failure occurs due to the combined effect of severe dyspnea and hypoventilation rather than peripheral muscle fatigue. Possibly, other factors may exist with different exercise protocols at different hypoxia degree. Therefore, further study is needed to explore the effect of exercise intensity on SA and SCM recruitment at moderate and severe hypoxic conditions.      78  Chapter Four: Summary and future directions  4.1 Summary Despite evidence of the long-term effect of inspiratory muscle training in healthy subjects and in patients with chronic respiratory disease, it is important to understand the etiology of respiratory muscle fatigue and reduced function. Respiratory muscle fatigue can be observed as a result of increasing ventilatory efforts above the threshold limit, such as during strenuous exercise in healthy subjects and moderate exercise in COPD patients with hyperinflated chest walls. Another condition in which respiratory muscle fatigue has been observed is during weaning from mechanical ventilation. Numerous studies have attempted to explain the causative factors of reduced respiratory muscle function. One of the common factors is hypoxemia, which might be elicited by exercise or other pathological components. However, few studies have assessed inspiratory neck muscle activity and fatigue during hypoxic conditions; to date, only one study has examined the changes in respiratory muscle oxygenation patterns of SCM. The primary objectives of chapter two were Objective 1 To determine the feasibility of spatially resolved NIRS to quantify the changes in oxygenation of SCM, PS and SA during incremental ITL in healthy adults. Hypothesis 1 We hypothesized that NIRS would be a feasible non-invasive tool to measure inspiratory muscle oxygenation during incremental ITL under normoxic and hypoxic conditions. 79  Findings   NIRS technology is considered a non-invasive method to measure change in tissue oxygenation. Quantifying change in limb muscle oxygenation using NIRS has been validated previously. Therefore, many researchers have utilized NIRS on muscles to investigate the pattern of oxygenation in healthy individuals and in patients under different conditions. In the field of rehabilitation and sports medicine research, muscle oxygenation has been estimated not only during normoxic exercise but also during hypoxic exercise. This experiment proves the feasibility of NIRS to measure inspiratory muscle oxygenation at different FIO2 levels. What is interesting in this finding is that spatially resolved NIRS is sensitive to very mild hypoxemia with SpO2 of around 95%. Therefore, regardless of the source of local tissue hypoxia, hypoxia can be easily determined by spatially resolved NIRS. Moreover, the numerical measure of TSI has a great advantage in clinical settings as it offers a simple, on-time measure that can be compared to normative values. Thus, this result must be seen as proof of concept.  Objective 2 To examine for the first time the combined effect of moderate hypoxia (FIO2  equal to15%) and ventilatory loading induced by ITL on inspiratory muscles oxygenation in healthy males and females.  Hypothesis 2 We hypothesized that the accessory inspiratory muscle, SCM, would deoxygenate, which manifests by a decrease in TSI prior to task failure during both ITL conditions. 80  Furthermore, these changes would be exaggerated during hypoxic ITL. Findings  As we expected, hypoxia accentuates inspiratory muscle deoxygenation during hypoxic ITL. However, the patterns of oxygenation were variable between muscles. In particular, SCM was the most vulnerable to deoxygenation that was demonstrated by a greater decrease in TSI and increase in HHb with minimal increase in O2Hb, whereas PS was able to compensate for the increase in HHb by maintaining a sufficient oxygen supply (O2Hb) and blood volume (tHb). It seems that SA has an intermediate response between SCM and PS. We postulated that the variation in muscles’ response to hypoxic ITL in regard to its oxygenation could be attributed to the difference in mechanical advantage distribution, muscle fiber composition and blood perfusion capacity (capillarization). With a similar objective, Katayama et al. (2015) have examined the effect of a severe hypoxic hyperpnea test on inspiratory muscle oxygenation. However, the magnitude of SCM was greater than the finding in this study. This presumably reflects the role of SpO2 saturation and the manner of exertion on local tissue oxygenation during exercise. It has been reported that the effect of hypoxia on skeletal muscle function depends on several factors including hypoxic dose, work rate, muscle prosperities, etc. (Perrey & Rupp, 2009). Collectively, it seems that the oxygenation pattern of skeletal and respiratory muscles is influenced by common factors in the hypoxic environment.   81  The primary and the secondary objectives of chapter three were Primary objective  To compare the EMG activation and signs of fatigue from SA and SCM during normoxic and hypoxic ITL of FIO2 equal to 15% in healthy adults. Primary hypothesis We hypothesized that the increase in inspiratory loads would result in increased SA and SCM activation. Moreover, hypoxic ITL would accentuate EMG activity and fatigue. Findings A study by Katayama et al. (2015) suggested the need to use multi-channel EMG electrodes  to minimize the impact of the heterogeneity of neural activation across muscle fibers and consequently enhance the estimation of EMG measurements. Based on this suggestion, we used array of EMG electrodes to detect SA and SCM activation.  The findings partially support the hypothesis revealing that both muscles, SA and SCM were progressively activated during normoxic ITL and, to a greater extent, during hypoxic ITL indicated by increased RMS. The increase in inspiratory neck muscle EMG activity during high ventilatory efforts reflects an increase of its contribution to ventilation. Moreover, the EMG amplitude of SA was significantly higher than that of SCM. The finding is consistent with findings of past studies  indicating that SA is an obligatory inspiratory muscle that has a greater mechanical advantage than SCM. In addition, SA is active during tidal breathing and high ventilatory loads, whereas SCM is inactive during 82  tidal breathing in healthy individuals. The other finding conflicts with our hypothesis, as peripheral muscle fatigue was absent after both ITL conditions. This was determined based on median frequency and inspiratory mouth pressure during MIP maneuvers. The finding suggests that inspiratory neck muscles  can compensate for a mild decrease in SpO2. The most appealing explanation for our findings is that task failure occurred before reaching the critical threshold of peripheral muscle fatigue. Furthermore, we attributed the lack of peripheral muscle fatigue to the study design. A key feature of this study is that breathing frequency and duty cycle were controlled with 2s inhalation and 4s exhalation.  Previous investigations have shown that breathing pattern has an influence on respiratory muscle fatigue and that a 33% duty cycle is below the fatigue threshold for the diaphragm (Sheel et al., 2001; St Croix et al., 2000). Therefore, it seems that the fatigue threshold for the extradiaphragm muscles is also above the 33% duty cycle. We postulated that the long relaxation period could enable adequate muscle recovery. Secondary objective To study the impact of acute hypoxia on ITL task failure. Secondary hypothesis We postulated that as consequence of muscle fatigue, hypoxic ITL would exaggerate dyspnea perception and reduce endurance. Findings  Despite a strong theoretical rationale for a selective hypoxic dose, our findings showed that healthy individuals could cope with a moderate reduction in FIO2.  Thereby, endurance, 83  which is the maximum load that can be achieved, was not affected by breathing a hypoxic gas mixture during ITL. Compensatory mechanisms may have occurred to provide a higher SpO2, in spite of the FIO2 of 15%. However, the occurrence of task failure at comparable ventilatory loads with the lack of muscle fatigue can be justified by a number of explanations. Many factors can contribute to task failure. Among the plausible explanations is that current evidence supports the existence of an inhibitory reflex of the central neural output. One of these reflexes is related to the amount of PETCO2. Several studies have examined the relationship between PETCO2 and task failure during resistive breathing exercises (Gorman et al., 1999; McKenzie et al., 1997). It has been shown that there is a strong correlation between the amount of the increase in PETCO2 and dyspnea perception, which may contribute to task failure. Moreover, these factors have been previously described as a protective mechanism preventing respiratory muscles against contractile fatigue. In the present study, PETCO2 and the dyspnea score were significantly higher at task failure than at baseline. However, no differences were observed in these measurements between the normoxic and the hypoxic ITL tests.  In summary, it appears that respiratory failure caused by respiratory muscle fatigue may have other contributing factors besides increased ventilatory loads in the presence of mild hypoxemia. Thus, the similarity in test performance is not surprising, as hypoxia did not accentuate inspiratory muscle fatigue, dyspnea and hypercapnia.     84  4.2 Future directions This research has raised many open questions in need of further investigations. The study shows that using NIRS in parallel with EMG provides advantageous insight about respiratory muscle function. Since the decrease in muscle TSI preceded muscle fatigue, it may imply pending muscle fatigue. Hence, further studies are needed to investigate the threshold zone that corresponds to both TSI reduction and muscle fatigue. More information about the correlation between NIRS and EMG would help us to establish a greater degree of accuracy in determining muscle function. In addition, the present data were obtained from healthy adults with a mean age of 31 years under the condition of hypoxia and increased ventilatory efforts. Perhaps aging and the presence of lung disease are critical confounding factors that many researchers have recommended taking  into consideration when studying exercise performance and respiratory muscle function. Considerably more work needs to be done to determine the recruitment pattern and the change in oxygenation of inspiratory neck muscles in the elderly and in patients with chronic cardiorespiratory diseases. It would be clinically relevant to compare the magnitude of inspiratory neck muscle activity in healthy subjects with hypoxemic patients. This may help to determine the normative values when monitoring critically ill patients.   Moreover, though we recruited male and female participants, they were not matched for the age and not equally distributed. Further studies should be carried out to explore sex differences in respiratory muscle oxygenation and recruitment by matching age and sex. 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Journal of Electromyography and Kinesiology, 10(5), 287–291.             128  Appendix A: Consent form           Incremental Inspiratory Threshold Loading in Healthy People during Normobaric Hypoxia and Normobaric Normoxia Principal Investigator:  Dr. W. Darlene Reid, BMR(PT), PhD, Department of Physical Therapy, University of British Columbia,  Investigator, Vancouver Coastal Health Research Institute Phone 604 875 4111 ext 66056 Co-investigator: Dr. Jayne Garland, PT, PhD, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada Phone 604-822-7414 Dr. Jeremy Road, MD, Respiratory Division, University of British Columbia  Phone 604-875-424 Dr. Babak Shadgan, MD, MSc, PhD Research Associate, Center for   International Collaboration on Repair Discoveries University of British Columbia Phone 604-603-6664 Nada Basoudan, BScPT, Masters Student, Rehabilitation Sciences, University of British Columbia Phone 604-875-4111 ext 6605                             Alessio Gallina, BScPT, MSc, PhD Graduate Student, Rehabilitation Sciences, University of British Columbia Phone 604-827-5372 For non-emergency contact number:  Dr. Reid at Phone 604 875 4111 ext 66056  Faculty of Medicine Vancouver Campus Department of Physical Therapy Muscle Biophysics Laboratory 617 – 828 West 10th Avenue Vancouver, BC Canada V6T 1Z3 Phone 604 875 4111 x 66056 129  1- Invitation You are invited to take part in this study that will examine the oxygen levels of the breathing muscles and how much they are used during a resistive breathing exercise in healthy adults. You are eligible if you are between 20 to 40 years or between 45 to 65, a non-smoker, healthy and your body weight score termed the body mass index score is between 18 to 25 Kg/m2 (not underweight nor overweight).  2. Your participation is voluntary  Your participation is entirely voluntary, so it is up to you to decide whether or not to take part in this study.  Before you decide, it is important for you to understand what the research involves.  This consent form will tell you about this part of the study, why the research is being done, what will happen to you during this part of the study and the possible benefits, risks and discomforts. If you wish to participate, you will be invited to sign this form.  If you do decide to take part in this study, you are still free to withdraw at any time and without giving any reasons for your decision.  3. Who is conducting this study?  This study is being conducted by investigators, Drs. Reid and Road, who are affiliated with Vancouver Coastal Health, Vancouver Coastal Health Research Institute and the University of British Columbia. None of the investigators will receive any personal payments for conducting the study. The study has been funded with support from the Royal Embassy of Saudi Arabia- Cultural Bureau in Ottawa.  4. Background Muscle can become fatigue from overuse such as running for long distances.  This can happen in leg muscles as well as in breathing muscles. The breathing muscles can be very prone to fatigue in people with chronic lung problems, especially in situations when they are being weaned off a breathing machine.  Therefore, health professionals are looking for non-invasive methods to early diagnose early signs of fatigue in these muscles.  We are doing our study on healthy people to get a better understanding of oxygen levels and the electrical activity of the breathing muscles during progressively greater loads.  Because people with chronic lung problems often have low oxygen levels in their blood, we are also interested to determine if the fatigue in the breathing muscles is accentuated by lowering the blood oxygen levels in the blood.   The oxygen levels in the blood will lower naturally when we breathe thin air at high altitudes.  We will mimic the oxygen levels at high altitude by having the participants breathe a gas mixture that has low oxygen levels.   5.  What is the purpose of the study? The purpose of the study is to determine whether new types of technologies provide more information about fatigue of the breathing muscles.  These technologies are an electromyography (EMG) that has multiple recording points and a device (near infrared spectroscopy-NIRS) that can estimate the levels of oxygen in tissue.  A second study purpose is to evaluate  breathing muscles tiredness and oxygen saturation levels  during a breathing test that requests subject to breathe though a mouth piece and against certain amount of loads. These loads are progressively increased as test intensity raise.. A third 130  purpose is to evaluate the effect of breathing exercise using a low oxygen gas mixture on these changes.  The low oxygen level will simulate one of the characteristics of a lung disease.  6. Who can participate in this study?   Healthy adult.  Aged 20 to 40 OR 45 to 65 years.  Body mass index greater than 18 and less than 25 kg/m2.  Able to provide informed consent.  7. Who should not participate in this study?   Smokers  People who have respiratory diseases or chronic illness like, neurological disorder, asthma, COPD  emphysema and heart disease ”e.g. a heart attack, heart surgery, cardiac catheterization, coronary angioplasty (PTCA), pacemaker/ implantable cardiac defibrillator/ rhythm disturbance, heart valve disease, heart failure, heart transplantation and congenital heart disease.  Overweight or underweight (body mass index  greater than 25 or less than 18Kg/m2).  People who suffer from skin hypersensitivity.  Elite athletes who are athletes with potential for competing in the Olympics or as a professional player or a national or international level player.  8. What does the study involve?  To determine eligibility for the study and to familiarize you to the testing procedures, you will partake in a screening visit.  The screening visit will be performed in a location convenient to you.  Next, you will participate in two testing visits separated by 4 to 6 days. The testing sessions will be performed in the Muscle Biophysics Laboratory at the Research Pavilion at Vancouver General Hospital. During these sessions, participants will be connected to device called near infrared spectroscopy (NIRS) and a multi-channel electromyography (EMG). You will be asked to do specific breathing exercise where you begin breathing against a light load and this is followed by a heavier load every 2 minutes. During your breathing exercise you will either breathe in room air (20.9 % of O2 concentration) and low oxygen gas mixture (15% of O2 concentration) which is equal to the oxygen concentration at 4000m above sea level.  During your first test session, one of these oxygen concentrations will be used and during the second visit the other oxygen mixture will be used.  If You Decide to Join this Study:  Specific Procedures The screening visit:  1. You will complete the questions that ask about your medical history and physical activity level.  2. Assessment of inspiratory muscle strength using handheld force meter where you breathe in as much force as possible.  3. Lung function test – where you breathe out as hard as possible. 131  4. Familiarization of breathing exercise. You will be asked to breathe using device that requires you to breathe in with more force.   You will be able to try this a couple of times at a couple of different levels. First test visit: 1. Assessment of inspiratory muscle strength.  2. Placement of NIRS and EMG electrodes on breathing muscles located on the front of your chest and the side of your neck as well as a muscle just to the outside of your shin bone. 3. You will be seated in an upright sitting position with feet and back supported, and forearms resting on a table at waist level. Head and neck will be supported by a head chin rest.   4. The oxygen mixture will be selected randomly using an online program that creates an arbitrary list of gas mixtures concentration (room air or low oxygen air). You will not be aware of the gas concentration when you are asked to breathe using mouthpiece against load where your nose closed with nose clip. The load increase every 2 minutes until you can no longer breathe against the higher loads. Figure 1 shows the breathing apparatus  5. Repeat the test of inspiratory muscle strength. 6.  You will be asked to stay with us for thirty minutes after you complete the test in order to measure the outcome during the recovery time. 7. You will be given a scoring sheet to indicate muscle soreness in your breathing muscles.  You will be asked to evaluate this at 4, 24 and 48 hours after the test.   Between the first and second visit: Three days after the first test visit, the Co-investigator will contact you to check your muscle soreness score and to confirm the date for the second test visit.   Second test visit:  It will be identical to the first visit except you will breathe a different gas mixture.  9.  What are my responsibilities?  To complete all visits  To refrain from caffeine for 12 hours and from exercise for 48 hours  10.  What are the possible harms and discomforts?   It is not likely that there will be any serious risks associated with the exercise protocols. During the exercise test you may feel uncomfortable, anxious or breathless or light-headedness.  After the test, you may experience muscle soreness in the muscles of their Figure 1: Breathing apparatus 132  neck, shoulders, and/or chest following the test, which is temporary and reversible over a couple hours to a couple of days   In case of an emergency during exercise, the room where the exercise takes place will be supplied with oxygen mask and ECG monitor. Also the exercise room is located less that 250 m to VGH emergency room. Therefore, the immediate response will be done by the principle investigator or the co- investigator, who are trained in CPR procedures, until the ambulance team come. Though the incremental inspiratory threshold loading protocol was established over that 25 years ago as safe procedure with no abnormal increase in heart rate or blood pressure. Moreover, many studies have administrated a gas mixture of 15% of oxygen concentration or below without any major side effect during both breathing exercises and whole body exercise  11. What are the potential benefits of participating?  There are no known potential benefits from participation in this study.  12.  What happens if I decide to withdraw my consent to participate?  Your participation in this research is entirely voluntary. If at any time you feel the need to withdraw from the study you are free to do so with no penalty. You may withdraw without providing any explanation of your reason for doing so nor will you lose the benefit of any medical care to which you are entitled or presently receiving. You do not have to submit a request to withdraw in writing.  If you choose to enter the study and then decide to withdraw at a later time, all data collected about you will be withdrawn upon your request and will be disposed of in a confidential manner.  13.  Can I be asked to leave the study? If you are not complying with the requirements of the study or for any other reason, the Principal Investigator may withdraw you from the study.  14. How will my taking part in this study be kept confidential? Your confidentiality will be respected. However, research records and health or other source records identifying you may be inspected in the presence of the Investigator or his or her designate by representatives of Clinical Research Ethics Board of the University of British Columbia for the purpose of monitoring the research. No information or records that disclose your identity will be published without your consent, nor will any information or records that disclose your identity be removed or released without your consent unless required by law.   You will be assigned a unique study number as a participant in this study. This number will not include any personal information that could identify you (e.g., it will not include your Personal Health Number, SIN, or your initials, etc.). Only this number will be used on any research-related information collected about you during the course of this study, so that your identity will be kept confidential. Information that contains your identity will remain only with the Principal Investigator and/or designate. The data you provide will be 133  kept in a locked cabinet where only research team will have access to it. Information kept on a computer will be protected by a password.   Your rights to privacy are legally protected by federal and provincial laws that require safeguards to insure that your privacy is respected. Further details about these laws are available on request to your study doctor.  15. What will the study cost me?  There are no costs associated with your participation.  If you complete the screening and the two testing visits, you will receive $ 50.  If you only complete the first testing session, you will receive $20.  16. Who do I contact if I have questions about the study during my participation?  If you have any questions or desire further information about this study before or during participation, or if you experience any adverse effects, you can contact Dr. Reid at   (604) 875-4111, ext. 66056.  17. Who do I contact if I have any questions or concerns about my rights as a participant?  If you have any concerns or complaints about your rights as a research participant and/or your experiences while participating in this study, contact the Research Participant Complaint Line in the University of British Columbia Office of Research Ethics by e-mail at or by phone at 604-822-8598 (Toll Free: 1-877-822-8598).   18. After the study is finished  If you would like to receive the result summary personally, please let me know how you would like us to send it to you. The results of this study will be reported in a graduate thesis and may also be published in journal articles.                  134             Incremental Inspiratory Threshold Loading In Healthy People during Normobaric Hypoxia and Normobaric Normoxia PARTICIPANT CONSENT  My signature on this consent form means:      I have read and understood the information in this consent form.     I have had enough time to think about the information provided.     I have been able to ask for advice if needed.     I have been able to ask questions and have had satisfactory responses to my questions.     I understand that all of the information collected will be kept confidential and that the results will only be used for scientific purposes.     I understand that my participation in this study is voluntary.     I understand that I am completely free at any time to refuse to participate or to withdraw from this study at any time, and that this will not change the quality of care that I receive.     I authorize access to my health records as described in this consent form.     I understand that I am not waiving any of my legal rights as a result of signing this consent form.     I understand that there is no guarantee that this study will provide any benefits to me.  By signing this form, you do not give up any of your legal rights and you do not release the study doctor, participating institutions, or anyone else from their legal and professional duties. If you become ill or physically injured as a result of participation in this study, medical treatment will be provided at no additional cost to you. The costs of your medical treatment will be paid by your provincial medical plan. ________________________  __________________________  Participant’s Signature    Printed name      Date   ________________________  __________________________  Investigator Signature    Printed name       Date    Faculty of Medicine Vancouver Campus Department of Physical Therapy Muscle Biophysics Laboratory 617 – 828 West 10th Avenue Vancouver, BC Canada V6T 1Z3 Phone 604 875 4111 x 66056 135  Appendix B: The American Heart Association and American College of Sport Medicine Health/ Fitness Facility Pre-participation Screening Questionnaire. Assess your health status by marking all TRUE statement History You have had -------- A heart attack -------- Heart surgery -------- Cardiac catheterization -------- Coronary angioplasty (PTCA) -------- Pacemaker/ implantable cardiac defibrillator/ rhythm disturbance -------- Heart valve disease -------- Heart failure -------- Heart transplantation -------- Congenital heart disease Symptoms ------- You experience chest discomfort with exertion ------- You experience unreasonable breathlessness ------- You experience dizziness, fainting, or blackouts ------- You take heart medication Other health issues ------- You have diabetes ------- You have asthma or other lung disease ------- You have burning or cramping sensation in your lower legs when walking short distance ------- You have musculoskeletal problems that limit your physical activity ------- You have concerns about the safety of exercise ------- You take prescription medications ------- You are pregnant  Cardiovascular risk factors ------ You are a man older than 45 years ------ You are a women older than 55 years, have had a hysterectomy or are postmenopausal ------ You smoke or quit smoking within the previous 6 months ------ You blood pressure is > 140/90 mm Hg ------ You do not know your blood pressure -------You take blood pressure medication  -------Your blood cholesterol level is >200 mg/dl -------You do not know your cholesterol level -------You have a close blood relative who had a heart attack or heart surgery before age 55 years (father or brother) or age 65 years (mothers or sister) ------- You are physically inactive (i.e., you get < 30 minutes of physical activity on at least 3 days/week) -------You are >20 pounds overweight -------None of the above   136  Appendix C: Modified Borg Dyspnea Scale.            137  Appendix D:Examination sheet  Name: ………………                                                               Phone: …………………… Address: ……………………………………………………    Age: ……………………..                                                                           Sex: ……………………..                                                         Weight: ……………….…. Height: ……………..                                                                             BMI: ……………….                                                                            Past medical history: …………….……………………………………………………………………………… Medication: …………………………………………………………………………………………… Spiromtric outcome measures:  first second third fourth fifth FVC      FEV1      FEV1/FVC      FVC % pred      FEV1 % pred       Skin fold thickness(mm): Muscle Right  left Placement  Scalene    SCM    Parasternal    Tibialis anterior     Note:                   138  Appendix E: Vital signs and dyspnea recording sheet  SpO2 Heart rate Blood pressure Dyspnea Baseline     2Min of unloaded     Load 1, 30 sec     Load 1, 60 sec  Load 1, 90 sec  Load 1,120 sec  Load 2, 30 sec     Load 2, 60 sec  Load 2, 90 sec  Load 2,120 sec  Load 3, 30 sec     Load 3, 60 sec  Load 3, 90 sec  Load 3,120 sec  Load 4, 30 sec     Load 4, 60 sec  Load 4, 90 sec  Load 4,120 sec  Load 5, 30 sec     Load 5, 60 sec  Load 5, 90 sec  Load 5,120 sec  Load 6, 30 sec     Load 6, 60 sec  Load 6, 90 sec  Load 6,120 sec  Load 7, 30 sec     Load 7, 60 sec  Load 7, 90 sec  Load 7,120 sec  Load 8, 30 sec     Load 8, 60 sec  Load 8, 90 sec  Load 8,120 sec  Load 9, 30 sec     Load 9, 60 sec  Load 9, 90 sec  Load 9,120 sec  Load 10, 30 sec     Load 10, 60 sec  Load 10, 90 sec  Load 10,120 sec   


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