Applied Science, Faculty of
Biomedical Engineering, School of
DSpace
UBCV
Wyss, Justin Kian Ming
Master of Applied Science - MASc
University of British Columbia
A pressure ulcer, also commonly referred to as a pressure injury or bedsore, is a localized injury or damage to the skin and/or underlying soft tissue, usually over bony prominences, due to prolonged pressure that is sufficient enough to impair blood supply. It is a wound that can disrupt an individual’s life abruptly, affecting not only the person’s physical and mental wellbeing, but also impacting the healthcare system significantly. Most susceptible to the development of a pressure ulcer are individuals confined to beds and/or wheelchairs. In the spinal cord injury (SCI) community, pressure ulcers remain one of the most prevalent and costly preventable secondary complications. There is a need for methods and/or devices that can reduce the incidences or even prevent the formation of such wounds, especially in bedridden patients and wheelchair users. We propose a soft, flexible, and stretchable capacitive pressure sensor array, made out of low-cost materials. It is scalable in size, robust and capable of measuring pressure in the desired range (0 – 200 mmHg) over extended periods of time (>12h) with low repeatability error (0.5%), hysteresis (0.57%), and non-linearity error (0.52%), while fully conforming around various contours (e.g. wheelchair cushions). The pressure readings are displayed on a generated pressure heatmap with the data being wirelessly transmitted to mobile devices (e.g. laptop, smartphone, tablet). A first iteration alert system design enables the sensor to be implemented for potential pressure ulcer prevention, warning the users and healthcare professionals prior to a formation. The working principle of the sensor is based on the well-established capacitance sensing technology, where the relative position of two electrodes is changed by applied force. The sensor array is made of soft, rubbery material and the dielectric contains air to enable relatively large deformations. Further work is required to improve the life-span of the sensor before it is ready to be tested with patients.
A SOFT FLEXIBLE AND STRETCHABLE PRESSURE SENSOR ARRAY DESIGNED TO WARN OF PRESSURE ULCER FORMATION by Justin Kian Ming Wyss B.A.Sc., The University of British Columbia, 2017 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (BIOMEDICAL ENGINEERING) THE UNIVERSITY OF BRITISH COLUMBIA (VANCOUVER) August 2020 © Justin Kian Ming Wyss, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled: A Soft Flexible and Stretchable Pressure Sensor Array Designed to Warn of Pressure Ulcer Formation submitted by Justin Kian Ming Wyss in partial fulfillment of the requirements for the degree of Master of Applied Science in Biomedical Engineering Examining Committee: Dr. John D. W. Madden, Electrical and Computer Engineering, UBC Supervisor Dr. Hendrik F. Machiel Van der Loos, Mechanical Engineering, UBC Supervisory Committee Member Dr. Babak Shadgan, Orthopaedics, UBC Supervisory Committee Member iii Abstract A pressure ulcer, also commonly referred to as a pressure injury or bedsore, is a localized injury or damage to the skin and/or underlying soft tissue, usually over bony prominences, due to prolonged pressure that is sufficient enough to impair blood supply. It is a wound that can disrupt an individual’s life abruptly, affecting not only the person’s physical and mental wellbeing, but also impacting the healthcare system significantly. Most susceptible to the development of a pressure ulcer are individuals confined to beds and/or wheelchairs. In the spinal cord injury (SCI) community, pressure ulcers remain one of the most prevalent and costly preventable secondary complications. There is a need for methods and/or devices that can reduce the incidences or even prevent the formation of such wounds, especially in bedridden patients and wheelchair users. We propose a soft, flexible, and stretchable capacitive pressure sensor array, made out of low-cost materials. It is scalable in size, robust and capable of measuring pressure in the desired range (0 – 200 mmHg) over extended periods of time (>12h) with low repeatability error (0.5%), hysteresis (0.57%), and non-linearity error (0.52%), while fully conforming around various contours (e.g. wheelchair cushions). The pressure readings are displayed on a generated pressure heatmap with the data being wirelessly transmitted to mobile devices (e.g. laptop, smartphone, tablet). A first iteration alert system design enables the sensor to be implemented for potential pressure ulcer prevention, warning the users and healthcare professionals prior to a formation. The working principle of the sensor is based on the well-established capacitance sensing technology, where the relative position of two electrodes is changed by applied force. The sensor array is made of soft, rubbery material and the dielectric contains air to enable iv relatively large deformations. Further work is required to improve the life-span of the sensor before it is ready to be tested with patients. v Lay Summary Pressure ulcers are a major health concern around the world, affecting individuals living with spinal cord injury (SCI) in particular. Pressure ulcers occur when the blood supply to the skin and underlying tissue is compromised, leading to cell death and potentially fatal infections. This thesis presents a soft, flexible, and stretchable pressure sensor array that is made of rubbery material. The array generates a pressure map and wirelessly transmits the data to mobile devices such as smartphones. It is shape-conforming, robust and demonstrates accurate pressure readings over many hours. A first iteration alert system design enables the sensor to be implemented for pressure ulcer prevention, with primary emphasis on wheelchair users. The performance of the sensor arrays has been tested. Further work is needed to evaluate performance with users. vi Preface All the research work presented in this thesis has been originally drafted and conducted by the author, under the supervision of Prof. Dr. John D. W. Madden, unless otherwise stated. The design, development, fabrication, analysis, and characterization of the sensor, as well as the design of the algorithm and alert system, has been conducted by the author. This thesis work is an extension of previous collaborative projects conducted during my time as an Undergraduate Research Assistant. This previous work was presented at the Materials Research Society Conference in 2015 titled “Hydrogel Based Flexible and Transparent Capacitive Proximity Sensor” and in 2017 titled “Soft Multi-Modal Sensor—Bend, Stretch, Pressure, Touch and Proximity Using a Gel Electrode Array”, and published in the journal Science Advances in 2017 titled “Bend, stretch, and touch: Locating a finger on an actively deformed transparent sensor”, led at the time by current post-doctoral fellow, Mirza Saquib us Sarwar. In Chapter 2, undergraduate students Sarah Mohn and Roshan Mishra aided with the fabrication of the stretchable electrode strips and measurement of the electrical conductivity, under the supervision of the author. Circuitry presented for the 4 x 4 sensor was developed prior to this work by Mirza Saquib us Sawar, whereas the circuitry presented for the larger sensor designs was developed by a capstone student team (4th year Electrical Engineering students, UBC), under the supervision of the author. PhD student Anindya Lal Roy aided with the analysis of the materials and completed, together with the author, the e@UBC’s Lean Launch Pad (LLP) program. Market research gained from this program is presented in Section 1.4. Undergraduate research assistant Daniel Zhou aided with the development of the software application for vii displaying the pressure heatmap, and the initial designs of the algorithm and alert system, under the supervision of the author. In Chapter 3, undergraduate research assistant Jason Chow aided with the fabrication and characterization of the sensor, and measurements and analysis of the “Ageing Effect” of the stretchable electrodes, under the supervision of the author. In Chapter 4, the collaboration work with visiting Master student Saki Tamura is described, which was presented at Material Research Society Conference in 2019 in a poster entitled “Woven Structure for Flexible Capacitive Pressure Sensors”. It was also published in MRS Advances (Soft Materials and Biomaterials) in 2020. viii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ....................................................................................................................... viii List of Tables ................................................................................................................................ xi List of Figures .............................................................................................................................. xii List of Abbreviations ...................................................................................................................xv Acknowledgements ................................................................................................................... xvii Dedication ................................................................................................................................. xviii Chapter 1: Introduction & Background ......................................................................................1 1.1 Thesis Motivation ........................................................................................................... 2 1.1.1 Pressure Ulcer Significance ........................................................................................ 2 1.1.2 Motivation ................................................................................................................... 6 1.2 Overview on Pressure Ulcers .......................................................................................... 9 1.2.1 Definition .................................................................................................................... 9 1.2.2 Etiology & Pathophysiology ..................................................................................... 10 1.3 Background on Prevention Methods, Sensing and the Proposed Approach ................. 21 1.3.1 Prevention Methods .................................................................................................. 21 1.3.2 Proposed Pressure Ulcer Sensing Technology ......................................................... 23 1.4 Entrepreneurship ........................................................................................................... 28 1.4.1 Customer Segment .................................................................................................... 28 ix 1.4.2 Competitive Landscape ............................................................................................. 29 1.4.3 Market Analysis ........................................................................................................ 31 1.5 Sensor Requirements .................................................................................................... 33 1.6 Thesis Objectives & Challenges ................................................................................... 34 1.7 Thesis Outline ............................................................................................................... 36 Chapter 2: Materials & Methods ...............................................................................................38 2.1 Introduction ................................................................................................................... 38 2.2 Working Principle ......................................................................................................... 40 2.3 Materials ....................................................................................................................... 46 2.4 Fabrication .................................................................................................................... 48 2.4.1 Electrodes .................................................................................................................. 48 2.4.1.1 Electrical Conductivity ..................................................................................... 49 2.4.1.2 cEcoflex Fabrication Process ............................................................................ 53 2.4.2 Pressure Sensor ......................................................................................................... 55 2.5 Electronics..................................................................................................................... 61 2.6 Algorithm ...................................................................................................................... 64 2.7 Alert System for Pressure Ulcer Prevention ................................................................. 66 2.8 Summary & Discussion ................................................................................................ 68 Chapter 3: Results & Discussion ................................................................................................70 3.1 Introduction ................................................................................................................... 70 3.2 Design & Architecture .................................................................................................. 71 3.3 Sensor Performance ...................................................................................................... 77 3.3.1 Pressure Measurements ............................................................................................. 77 x 3.3.2 Signal-to-Noise Ratio................................................................................................ 85 3.4 Further Investigation of cEcoflex ................................................................................. 87 3.4.1 Ageing Effect ............................................................................................................ 87 3.5 Dimensional Scaling ..................................................................................................... 93 3.6 Resolution & Pressure Heatmap Visualization ............................................................. 95 3.7 Summary & Discussion ................................................................................................ 98 Chapter 4: Conclusion & Future Work ...................................................................................103 4.1 Conclusion .................................................................................................................. 103 4.2 Limitations .................................................................................................................. 105 4.3 Future Directions ........................................................................................................ 106 Bibliography ...............................................................................................................................109 Appendices ..................................................................................................................................119 Appendix A – Sensor Design Iterations .................................................................................. 119 xi List of Tables Table 1: Potential annual cost avoidance with 20% reduction of pressure ulcer incidence ........... 8 Table 2: Pressure ulcer main risk factors ...................................................................................... 13 Table 3: Competitive landscape .................................................................................................... 30 Table 4: List of desired sensor specifications ............................................................................... 33 Table 5: List of specification obtained by our sensor ................................................................... 99 Table 6: Comparison table of desired and obtained specifications ............................................. 104 xii List of Figures Figure 1: (A) Reswick and Rogers pressure-time curve, (B) Clinical implication of using sigmoid injury threshold ............................................................................................................................. 11 Figure 2: Visualization of most susceptible locations to the formation of PUs ............................ 12 Figure 3: Stage I pressure ulcer .................................................................................................... 15 Figure 4: Stage II pressure ulcer ................................................................................................... 16 Figure 5: Stage III pressure ulcer .................................................................................................. 17 Figure 6: Stage IV pressure ulcer.................................................................................................. 18 Figure 7: Stage X (unstageable) pressure ulcer ............................................................................ 19 Figure 8: Deep tissue pressure injury ............................................................................................ 20 Figure 9: Pressure sensor demonstrating flexibility, stretchability, and shape conformability. ... 24 Figure 10: Market size for pressure ulcer treatment product (2026) and market size for pressure relief devices (2025) ..................................................................................................................... 31 Figure 11: Market size for pressure relief cushion with integrated pressure sensor ..................... 32 Figure 12: Block diagrams showing the abstraction layers .......................................................... 39 Figure 13: Parallel plate capacitor with electric field representation ........................................... 42 Figure 14: Working principle of pressure sensor .......................................................................... 42 Figure 15: The four-element Burgers model ................................................................................ 45 Figure 16: Strain-time behaviour of the Burgers model ............................................................... 45 Figure 17: Cross sectional view of main sensor architecture ....................................................... 47 Figure 18: Conductivity experiment set-up .................................................................................. 50 Figure 19: Conductivity of cEcoflex with varying wt.% of carbon black in Ecoflex .................. 52 xiii Figure 20: cEcoflex electrode strips patterned on base layer post doctor blading process ........... 54 Figure 21: Simplified fabrication process of the sensor broken down into three main steps ....... 55 Figure 22: Detailed fabrication process of the sensor .................................................................. 58 Figure 23: Sensor-to-readout circuit board connection ................................................................ 59 Figure 24: Cylindrical pillars aligning with cEcoflex electrode strips ......................................... 59 Figure 25: Read-out circuit board for the small 4 x 4 sensor........................................................ 62 Figure 26: Read-out circuit board for 32 x 32 sensors .................................................................. 63 Figure 27: Flowchart describing the operation of the algorithm in assessing and storing data .... 65 Figure 28: Alert system overview ................................................................................................. 67 Figure 29: Dielectric architecture - Cylindrical Pillars ................................................................. 71 Figure 30: Cross-sectional view of 4 x 4 pressure sensor. ............................................................ 72 Figure 31: Stress-Strain plots of pressure sensor with cylindrical dielectric structure ................. 74 Figure 32: Strain-time behaviour of pressure sensor .................................................................... 75 Figure 33: Repeatability and accuracy experiment on sensor design ........................................... 75 Figure 34: Experimental set-up on Bose ElectroForce with load cell and 3D printed indenter. .. 77 Figure 35: Sensor performance with varying pressures magnitudes (I) ....................................... 79 Figure 36: Sensor performance with varying pressures magnitudes (II) ...................................... 80 Figure 37: Sensor performance with varying pressures (III) ........................................................ 80 Figure 38: Capacitance plot of 4 x 4 sensor showing all 16 sensing taxelst ................................. 82 Figure 39: ΔC over Pressure hysteresis plot ................................................................................. 83 Figure 40: Performance of an ageing pressure sensor .................................................................. 87 Figure 41: Experimental set-up for measuring resistance change in cEcoflex ............................. 89 Figure 42: Resistance measurements of cEcoflex electrodes on three different substrates .......... 90 xiv Figure 43: Characterized medium size pressure sensor with pressure heatmap on smart phone . 96 Figure 44: Testing the resolution of the medium size pressure sensor ......................................... 97 Figure 45: First fabric-based pressure sensor iteration ............................................................... 108 Figure 46: Cylindrical pillar design and performance plot ......................................................... 120 Figure 47: Hollow cylindrical pillars "Life Savers" design and performance plot ..................... 120 Figure 48: Cylindrical pillars and "Life Saver" combinations design and performance plot ..... 121 xv List of Abbreviations BC – British Columbia BFSL – Best Fit Straight Line BT – Bluetooth CAPU – Community-Acquired Pressure Ulcer CDC – Capacitance-to-Digital Converter DR – Dynamic Range FS – Full-Scale HAC – Hospital-Acquired Condition ICU – Intensive Care Unit IDC – Insulation-Displacement Contact IEC – International Electrotechnical Commission LLP – Lean Launch Pad LUT – Look-Up Table MUX – Multiplexer NA – North America NPUAP – National Pressure Ulcer Advisory Panel PDMS – Polydimethylsiloxane PMT – Pressure Mapping Technology PU – Pressure Ulcer PUP – Pressure Ulcer Prevention xvi RMS – Root Mean Squared RSS – Root of the Sum Squared SCI – Spinal Cord Injury SNR – Signal-to-Noise Ratio UBC – University of British Columbia VGH – Vancouver General Hospital xvii Acknowledgements I would like to express my gratitude and thank my supervisor, Prof. Dr. John D. W. Madden, for all his endless support and guidance throughout my time at the Molecular Mechatronics Laboratory, and by giving me the opportunity to pursue my goals in Biomedical research and entrepreneurship. I would also like to acknowledge and thank my supervisory committee members, Prof. Dr. Babak Shadgan and Prof. Dr. Machiel Van der Loos, for taking the time for discussions and guiding me through my research, my clinical advisors at ICORD, GF Strong and Praxis Spinal Cord Institute, for giving me first-hand shadowing experiences and counseling, my team (Anindya Lal Roy, Jason Chow, Daniel Zhou, Yuta Dobashi) for assisting me with my work throughout, as well as my lab members. I am grateful to the School of Biomedical Engineering at The University of British Columbia and all personnel for providing such an amazing environment for us students and giving us the platform to thrive in our fields of study, the Natural Sciences and Engineering Research Council of Canada (NSERC) for funding my research, and all my colleagues, lab mates and friends for the great fun and experiences spent together on and off campus. Special thanks goes to Dr. Mirza Saquib us Sarwar, who was there since my undergraduate days. A good friend and mentor. Finally, my biggest gratitude goes to my family, who have supported, encouraged and inspired me throughout my life. Words cannot do it justice. Thank you! xviii Dedication I dedicate this thesis to my amazing parents and brothers. In hopes that this work may contribute in any way to the prevention of pressure ulcers and help individuals susceptible and/or affected by it to ease and lighten the burden and ultimately improve their quality of life. 1 Chapter 1: Introduction & Background In this thesis, we will be exploring a soft, flexible, and stretchable tactile sensing array (sensing mat), developed and fabricated in the Molecular Mechatronics Laboratory at The University of British Columbia (UBC), aimed to tackle the healthcare issues surrounding pressure ulcers (PUs) with an initial emphasis on the spinal cord injured (SCI) population. This work was conducted with guidance and consultation from healthcare professionals and experts at the Vancouver General Hospital (VGH), GF Strong Rehabilitation Centre, and the Praxis Spinal Cord Institute. 2 1.1 Thesis Motivation 1.1.1 Pressure Ulcer Significance PUs, also commonly referred to as pressure injuries, bedsores, or decubitus ulcers, are considered a serious health condition - one of the most costly, preventable, and physically debilitating conditions of the 20th century, affecting millions around the globe [1], [2], [3], [4], [5], [6]. Most vulnerable to the development of PUs are people who are immobile, confined to beds and/or wheelchairs due illness, injury, or age [7]. PUs are painful and discomforting, particularly to those whose sensorimotor feedback systems are still intact. They can get so severe and deep, exposing muscle and bone (Stage IV PU) and causing such immense damage, that they can result in life threatening infections, such as sepsis and osteomyelitis [8], [9]. They are most commonly found as a community-acquired pressure ulcer (CAPU), hospital-acquired condition (HAC), or as a secondary health complication amongst SCI individuals. Today, PUs remain the only HAC that is still on the rise [10]. Hospital stays associated with PUs (primary and secondary PUs) were also shown to be almost three times longer than cases without the diagnosis of PUs, reaching on average 14.1 days (principally PU) compared to 5.0 days (no PU) [11]. In the United States (US), approximately 2.5 million patients annually develop a PU, from whom approximately 60,000 die due to infections [12]. According to recent findings, PUs have a higher mortality rate in the US than any cancer, except for lung cancer [13]. They are costly to treat, placing them third in total annual expenditures behind cancer and cardiovascular diseases [2]. In the US, it is estimated that $11 billion dollars is spent annually on PUs [11], [14], with some sources projecting the cost to rise up to approximately 3 $26.8 billion a year [13]. The hospital cost per PU patient was averaged to be $48,000, where the average treatment cost for a Stage IV hospital acquired pressure ulcer (HAPU) was approximately $129,248, and a community-acquired pressure ulcer (CAPU) $124,327 [15]. The incidence rate (the rate of new cases occurring over a specific time period, commonly per year) of PUs varies by country and by clinical setting. In the United States the incidence rate ranges from 0.4% to 38% in inpatient acute care, from 2.2% to 23.9% in long-term care and skilled nursing facilities, from 0% to 17% in home care, and from 10% to 41% in intensive care units (ICUs) [2], [16]. The prevalence rate (the proportion of people with pressure ulcers in a population at some point in time) was reported to be ranging from 3.5% to 69% [2], where in the acute care setting this rate was shown to be 15% [17]. The overall prevalence rate across all healthcare institutions in Canada, as reported in 2004, is estimated to be 26% (95% CI, 25.2% to 26.8%), with approximately half of them being described as a Stage I pressure ulcer [6], [17]. This overall estimation of prevalence is shown to be higher than estimates from European hospitals, which have reported to be ranging from 8.3% to 23% [18], [19]. In the SCI community, PUs manifest a substantial problem where an estimate of 95% of individuals with SCI will develop at least one PU in their lifetime [20] with approximately 40% occurring during the first three-years post injury [21]. Most people with SCI develop a PU in community settings. It is argued that the risk of forming a PU increases after discharge from acute or rehabilitation care, meaning that a CAPU is more likely to develop for them than a HAPU [20], [22]. The annual incidence of PUs in the SCI population is shown to range from 15% to 30% [21], where the risk in community-dwelling individuals with SCI can be as high as 29% [20], [23]. The prevalence of PUs varies from 8% to 40% [22], with 27.8% prevalence reported for Canadian community settings [24]. In Canada, there are approximately 86,000 4 people living with SCI (51% traumatic SCI and 49% non-traumatic SCI), with roughly 4,300 new cases each year [25], [26]. The annual direct healthcare cost in Canada for treating PUs within the traumatic SCI population is suggested to be more than to $365.7 million CAD, with individual PU cases reaching as much as $400,000 CAD to heal and close [20]. In the province of British Columbia (BC), it is estimated that there are more than 6,000 individuals living with traumatic SCI and that each year 23% (incidence rate) of that population will experience one or more PUs. The distribution of PUs by stages was assumed to be as follows: Stage I (50.62%), Stage II (38.76%), Stage III (7.34%), and Stage IV (3.28%). The annual direct healthcare cost in BC exceeds $49 million CAD, where the average cost for treating PUs (Stage I – IV) is $35,592 CAD with a Stage I PU costing on average $12,108 CAD and a Stage IV PU $120,062 CAD [20]. The impact of PUs is vast and severe, affecting not only the patients and their families, but also the healthcare and legal systems. Beside the financial burdens, there are human costs associated with this disease. For the SCI population, the main burdens (P. Clarke-Richardson, personal communication, 2018) after developing a PU are as follows [11], [27], [28]: • Longer hospital stays & repeated clinical visits; • Lengthy immobilization often face-down; • Complete reliance on care-givers – loss of independence; • Long delays for specialist treatment; • Major surgeries including amputations, with risk of death; • Higher risk of PU recurrence after initial development; • Loss of productivity and financial income; 5 • Constant dressing changes; • Mental health – depression, social isolation, lack of confidence, fear, anxiety; • Family members cost – time, money, work, mental health. Given these effects on the individuals and on society, I am motivated to help reduce the incidence of pressure ulcers. 6 1.1.2 Motivation Despite the knowledge obtained throughout the years around PUs and their associated risk factors, which led to ever evolving advancements in management, treatment and prevention, incidence rates keep rising every year. This continuous presence of PUs, which is usually deemed as a performance measure in hospitals and care facilities, indicates that there is still much room for improvement, especially when it comes to prevention. As of yet, there is no true gold standard for prevention or treatment of this complex chronic wound [29]. Current solutions for “preventing” PUs are based on conventional risk assessment scales and direct approaches of alleviating risk factors [2], [30]. The most common method being frequent turning and re-positioning of immobile patients to reduce prolonged pressure over localized areas [31], [32]. Due to the limitations and costs of turning schedules, pressure reducing devices emerged to assist with the prevention, such as support cushions for wheelchairs and viscoelastic mattresses for beds. These devices have demonstrated distinct improvement, lowering the incidence of PUs in hospitals by approximately 60% [18]. However, they do not prevent PUs from forming but rather delay the formation process. For wheelchair cushions, it was shown that most seat cushions were not ideal or able to lower the pressure applied below the arterial capillary level, especially over the ischial tuberosity [33], which is the rounded bone that extends from the ischium. It is also commonly referred to in pairs as the sitting bones. In addition to these pressure relief devices, pressure mapping technology (PMT) have been used to address PUs [34], [35]. This technology captures the weight distribution across a sensor array and visualizes the data to educate at-risk individuals and provide healthcare professionals with more data for diagnosis purposes. These devices are expensive, making them unaffordable for home 7 and widespread hospital use, and are not fully shape-conforming, which leads to loss in comfort, accuracy and robustness. They are also inadequate in terms of measuring low- and high-pressure over long periods of time, especially for the SCI population in wheelchairs, which is a primary concern (R. Hickling, personal communication, 2017). During my shadowing experiences at VGH and GF Strong, I discovered that healthcare facilities do not use PMTs for long pressure measurements, but rather just for a maximum of 15-minutes for quick assessment and educational purposes. After a certain amount of time, it seems that these expensive PMT devices show performance issues (S. Sproule, personal communication, 2017), meaning that they cannot be used for continuous measurements on wheelchairs. As the cost of PMTs is an issue, they are not used to replace skin inspections and largely serve as an educational tool only. In Section 1.3, current prevention methods are further discussed. A technology that can help reduce or even completely prevent PUs from forming will have an immense impact on the healthcare system and everyone associated with this chronic wound. Taking into account just the SCI population in Canada, with a 20% reduction of PU occurrences, the potential cost-avoidance is estimated to be around $71.1 million CAD, as outlined in Table 1 below. This increases linearly to $106.6 million CAD for 30% and $142.2 million CAD for 40% PUs reduction [21]. 8 The reduction in suffering and in economic costs associated with limiting the occurrence of pressure ulcers is what motivates my work. Before presenting my approach, I will first provide some additional background on pressure ulcers. Table 1: Potential annual cost avoidance with 20% reduction of pressure ulcer incidence. Republished with permission of Praxis Spinal Cord Institute Copyright ©2011 [21] 9 1.2 Overview on Pressure Ulcers 1.2.1 Definition PU is a disease described in Ancient Egypt [2]. It is commonly referred to as a bedsore, decubitus ulcer, pressure necrosis, or ischemic ulcer, but most recently as a pressure injury, so named by the National Pressure Ulcer Advisory Panel (NPUAP) in 2016 [36]. This new terminology is preferred as it better reflects all the stages and forms of tissue damage caused due to pressure. However, in this thesis we will continue to use the term pressure ulcer (PU), as it still the most common and widely accepted terminology. A PU has been defined by the European Pressure Ulcer Advisory Panel (EPUAP) and the NPUAP as “a localized injury to the skin and/or underlying tissue usually over a bony prominence as a result of pressure, or pressure in combination with shear and/or friction”. Some researchers believe that this definition is not satisfactory as it does not describe the whole picture. They further refined the definition of PUs as “an area of localized soft tissue ischemic necrosis caused by prolonged pressure higher than the capillary pressure with or without shear, related to posture, which usually occurs over a bony prominence” [2]. 10 1.2.2 Etiology & Pathophysiology PUs remain a major health concern for people with SCI and individuals confined to beds due to illness, injury or infirmity. The main cause of PUs is believed to be the inadequate relief of pressure. As defined earlier in this thesis, uninterrupted pressure to the skin above the capillary pressure of ~ 32 mmHg is the main contributing factor of PUs, as it occludes the blood flow, leading to local ischemia and in turn making the underlying and surrounding tissues become anoxic. PUs will develop if the applied pressure continues, passing a critical duration, which will result in soft tissue necrosis and eventually ulceration [2], [7], [37]. The time for a pressure ulcer to form is still uncertain and currently at best a generalization. This is due to the many risk factors (extrinsic and intrinsic) associated with PU formation, making each case unique. The most cited paper about the onset of PUs is the retrospective study by Reswick and Rogers in 1976 [38]. They show that there is an inverse relationship between pressure and time, indicating that applications of high pressure for short duration can form PUs. However, in Gefen et al. it is claimed that the pressure-time curve of Reswick and Rogers is flawed and inaccurate in the extremities, stating that it is not suitable for predicting deep tissue injury (DTI) or any PU [39]. An alternate pressure-time curve was presented by Linder-Ganz et al., which provides better defined limits, in the form of a sigmoid mathematical function. The difference between the two curves is that Reswick and Rogers data refers to the interface pressure, whereas Linder-Ganz et al. data refer to pressure applied directly to muscle tissues [40], [41]. In Figure 1, a representation of the two curves is shown. 11 Figure 1: (A) Reswick and Rogers pressure-time curve compared with the sigmoid injury threshold, (B) Clinical implication of using the sigmoid injury threshold. Republished with permission of RCNi, from Reswick and Rogers pressure-time curve for pressure ulcer risk. Part 2., Gefen, 23, 46, 2009 [40]; permission conveyed through Copyright Clearance Center, Inc. 12 Areas most susceptible to PU formation are bony prominences, such as ischial tuberosities , heels, tailbone, hips, elbows, ankles, shoulder blades, and the back of the head (Figure 2) [7], [42]. Roughly 95% of PUs occur in the lower part of the body, with the ischial tuberosities being the most prone areas for individuals with SCI [24], [43]. In general, PUs form more often in people who are sitting rather than lying down, as the pressure exerted on the bony prominences is greater. Figure 2: Visualization of most susceptible locations to the formation of PUs Republished with permission of informedhealth.org/IQWiG 13 Risk Factors There are many intrinsic and extrinsic factors that have an impact on the formation of PUs. The main causative factors are the extrinsic ones, with “pressure” leading the group, while intrinsic factors play the second fiddle to the formation of PUs. They are also referred to as secondary factors in the development of PUs. In Table 2, the main risk factors are listed [2], [42]. Table 2: Pressure ulcer main risk factors Extrinsic Factors Intrinsic Factors Others Pressure SCI Long Surgeries Shear Neurological Diseases Prolonged Hospital Stay Friction Diabetes, Atherosclerosis PU Recurrence Moisture Age, Gender, Race No Support Cushion / Mattress Body Posture Fragile Skin Immobility Anemia, Edema Metabolism, Nutrition Other Acute & Chronic Illness 14 Pressure Ulcer Stages The National Pressure Ulcer Advisory Panel (NPUAP) has classified PUs into six stages/categories [44]: • Stage I • Stage II • Stage II • Stage IV • Stage X - Unstageable • Suspected Deep Tissue Injury (sDTI) The definition of each stage is described and visually represented below. 15 Stage I Stage I PUs are characterized by intact skin with localized superficial reddening (non-blanchable erythema), as shown in Figure 3. This PU may differ in temperature, consistency, and tenderness compared to the surrounding healthy tissue. Figure 3: Stage I pressure ulcer - (A) Stage I pressure ulcer shown next to healthy skin, (B) Comparison of blanchable and non-blanchable skin. Republished with permission of NPUAP Copyright ©2016 16 Stage II Stage II PUs are characterized by partial-thickness loss of the skin with exposed dermis. The ulcer is superficial and is presented clinically as a blister. Figure 4: Stage II pressure ulcer shown next to healthy skin Republished with permission of NPUAP Copyright ©2016 17 Stage III Stage III PUs are characterized by full-thickness loss of the skin, as shown in Figure 5. Adipose (fat) is visible in the ulcer with granulation tissue and epibole (rolled wound edges) often present. Undermining (pocket beneath the skin at the wound’s edge) and/or tunneling (channels that extend from the wound into or through subcutaneous tissue or muscle) may occur. The depth of tissue damage varies by anatomical location. Figure 5: Stage III pressure ulcer shown next to healthy skin Republished with permission of NPUAP Copyright ©2016 18 Stage IV Stage IV PUs are characterized by full-thickness loss of the skin and tissue with exposed muscle, tendon, ligament, cartilage, or bone in the ulcer. Undermining (pocket beneath the skin at the wound’s edge) and/or tunneling (channels that extend from the wound into or through subcutaneous tissue or muscle) often occur. The depth of tissue damage varies by anatomical location. Figure 6: Stage IV pressure ulcer shown next to healthy skin Republished with permission of NPUAP Copyright ©2016 19 Stage X - Unstageable Unstageable PUs are characterized by obscured full-thickness loss of the skin and tissue. The extent of tissue damage within the ulcer cannot be confirmed due to slough and eschar. Once removed, a Stage III or IV PU will be revealed. Figure 7: Stage X (unstageable) pressure ulcer shown next to healthy skin Republished with permission of NPUAP Copyright ©2016 20 Deep Tissue Pressure Injury Deep tissue pressure injuries are characterized by persistent non-blanchable (deep red, maroon, or purple) discoloration. The skin may be intact or non-intact with a localized area of persistent discoloration. Figure 8: Deep tissue pressure injury - (A) Stage I pressure ulcer shown next to healthy skin, (B) Comparison of blanchable and non-blanchable skin Republished with permission of NPUAP Copyright ©2016 21 1.3 Background on Prevention Methods, Sensing and the Proposed Approach 1.3.1 Prevention Methods Over the years, treatment and prevention methods have evolved, and there many different methods of management of PUs as a wound. However, there is still no true gold standard when it comes to prevention. In this thesis, we will touch upon the few main methods of prevention currently used. Conventional Prevention To prevent PUs from developing, it is essential to take care of the risk factors, “pressure” being the main causative factor. The most conventional method for preventing PUs is a scheduled re-positioning of patients, as well as educating people with paraplegia to readjust their position to relieve pressure while sitting on wheelchairs. In hospital settings (e.g., ICUs), common practice is to turn a patient every 2 hours [45], whereas SCI individuals, who are able to readjust, are instructed to re-position every 15 minutes (S. Sproule, personal communication, 2018) [46]. This method is precautionary and not as effective as one might hope. In addition, there is the use of the different assessment scales that healthcare professionals use to determine the risk of PUs (Norton, Waterlow, and Braden Scales). These scales assess and rate a variety of different risk-factors and skin conditions based on observation and health information [2]. 22 Modern Prevention Due to the limitations and cost of turning schedules, pressure reducing devices and pressure mapping technologies (PMTs) emerged to assist with prevention. For wheelchair users, it is common to have a support cushion that re-distributes the pressure. These come in different materials such as foam, air, gel, etc., and are mostly static with some exceptions (dynamic). The static cushions show promise in delaying the process of PU formation but overall do not prevent PUs. In a study where a variety of static cushions have been tested, it was shown that none of the cushions were deemed safe for prolonged sitting, as PUs eventually will form over time [33]. The dynamic cushions intend to interrupt the constant pressure experienced by the user with actuation of individual cells inside the cushion, preventing the formation of PUs. These actuations are pre-set, which can cycle up to 60 times per hour [47]. Further investigation is required to determine whether this device can be deemed a prevention device for PUs, as there are many other risk factors to consider. Due to unnecessary adjustment to the user, there is a probability of creating new risk areas, where PUs can form as a result of shear and/or friction. PMTs have been used to provide healthcare professionals with more data for assessment and diagnosis purposes. They are commonly used to assess the risk of ulcer formation, where a sensor pad is placed between the patient and a surface, and force distribution is visualized using software. PMT can be a powerful patient education tool, helping wheelchair users determine how far back they should tilt their chairs for effective pressure relief, or helping bedridden patients learn how to reposition themselves to minimize forces on the skin. However, these PMTs are not used for prevention purposes. The majority of these device are not designed to measure pressure over long periods of time, especially not in wheelchairs (S. Sproule & I. Denison, 2018 & 2019). 23 1.3.2 Proposed Pressure Ulcer Sensing Technology Over the years, sensing technologies have advanced, becoming soft, flexible, and stretchable, enabling new applications in artificial skin [48], robotics [49], sports [50], healthcare [51], smart textile clothing [52], etc. These compliant sensors are made possible with the use of different conducting materials for the electrodes, such as liquid metal [53], silver nanowires [54], conducting polymer [55], [56], [57], and hydrogel [57], [58], [59], providing appealing features to the soft sensors including in some cases stretchability. Together with healthcare professionals and experts in the field of wounds and SCI at VGH, GF Strong, and Praxis Spinal Cord Institute, we set our goal to develop a new sensing device (sensing grid array), based on recent advancements in soft sensors, that can tackle the problems of PUs, with the main emphasis firstly directed towards the SCI population in wheelchairs, by being low-in-cost, shape-conformable, pressure sensitive and accurate over long time periods, and improving the early detection of PUs, taking a step closer to a prevention system. In this thesis, we aim to innovate towards a better care of wheelchair users throughout Canada, with potential to generate new applications with the underlying technology and to address wider populations. A low-cost, tactile sensor array is developed that generates a pressure map and wirelessly transmits the data to a mobile device (e.g., smartphone). Unlike other products such as the aforementioned PMTs, our sensor is designed using soft, elastomeric materials, which makes the sensor flexible, stretchable and highly robust. It also makes the sensor fully shape-conforming, as shown in Figure 9, which should give an accurate representation of the contact between the patient and the surface, whether on a bed or wheelchair cushion. The hope is that the accuracy 24 and functionality will enable early warning and prevention of pressure ulcers, while the affordability of this device will allow widespread use, thereby reducing the incidence of PUs in Canada and mitigating their serious impact on those individuals affected, as well as on the healthcare system. Figure 9: Pressure sensor demonstrating flexibility, stretchability, and shape conformability. (A) Sensor flexibility shown by wrapping around a wooden cylindrical rod with 5 mm diameter (bending radius of curvature of 2.5 mm), (B) Sensor being stretched by hand reaching a strain of > 50%, (C) Arbitrary shape, (D) Sensor conforming around arbitrary shape, (E) Sensor demonstrating shape conformability while being actively compressed by finger. 25 The technology described in this thesis is designed to be part of an early PU warning system, intended for wound care management and prevention. It consists of an array of capacitive sensors with associated electronics including a wireless transmitter. The system comprises a tri-layer sensing device incorporating soft elastomers and conductive electrode materials with an architecture designed to detect pressure in the range of 0 mmHg to 200 mmHg. The soft, flexible and stretchable design of the technology is intended for long-term use and to give an accurate representation of the contact between the patient and the surface of the sensor array. The data assessment algorithm and pressure mapping software analyzes and displays the pressure data over time to develop a real time, quantitative, visual representation of the data as it corresponds to each sensor location in the array. The initial end-users of the product would be those who are partially or fully immobilized, particularly those using wheelchairs, or spending long periods in beds. Other potential customers include hospital outpatients, hospital inpatients, those in domiciliary care, and those ageing in place. The electronics are directly connected to the sensor and attached on the side of the wheelchair or bed. The power consumption of the current device is low (< 5 mW), allowing it to be powered by common off-the-shelf batteries. Ideally, we would want to be able to measure pressure distribution over the entire day, meaning for our device to be in continuous operation for 24 hours. With the current system, it is to be expected to last up to 4 months without recharging with a standard phone battery. We envision that with future design iterations of our circuitry, we can even further optimize the average power consumption. Alternatively, it can be powered from a power outlet or power wheelchair. 26 While this thesis covers the initial design and lab characterization, the ultimate envisioned use of our sensor would be to place power in the hands of the afflicted individuals, giving them control over their health by letting them monitor their pressure distribution throughout the day, and make adjustments to position or behaviour in order to lower the risk of ulcer formulation. In addition, the device might be used as a research, education and assessment tool in clinics, potentially improving the accuracy of the pressure-time curve of PUs. By incorporating an alarm system, the end-user and healthcare professionals may be alerted prior to a Stage I PU, preventing early formation. Expected Advantages of the Proposed Design: 1) Inexpensive materials and scalable fabrication processes: The device is aimed to be affordable to end-users, healthcare professionals and institutions. Its estimated material cost is ~$15/unit, which includes the elastomers and conductive material. By considering the electronics, software, and cost of fabrication, the overall cost of this product (~$200/unit) is substantially lower than current PMT solutions (>$6,000/unit, plus additional cost for software, up to $26,000). 2) Shape-conforming materials: The device should conform to the user’s body, giving an accurate representation of the contact between the patient and the surface of the sensor array. It is homogeneous with a smooth surface suitable for long-term use, unlike current devices that contain rigid materials and/or are not stretchable. 27 3) Algorithm: The device should have the ability to detect movement patterns, identify at-risk locations, count high impact areas and ideally generate patient-specific recommendations based on movement patterns. This last goal will require more work in the future. 4) Compatible with Android and iOS: This affords ease-of-use and portability using mobile devices, and eliminates the requirement for a computer. 5) Potential for disposable applications: Using low-cost methods and materials, we see the potential to reduce the cost of our sensor technology substantially, opening the door to applications such as disposable sensor sheets for beds, wheelchairs and other settings. This can help avoid time-consuming cleaning processes that hinder healthcare professionals to attend to other patients. The sensor materials might also be made biodegradable, so the environmental impact of disposable products is limited. Expected Disadvantage of the Proposed Design: 1) Electrode Ageing Effect: The current stretchable electrode described in this thesis is promising in terms of physical properties; however, it shows signs of “ageing”, making the sensor behave abnormally in its measurements even sometimes a few days post-fabrication. This effect needs to be further investigated but seems to show that our sensor has a finite lifespan. This “Ageing Effect” is further discussed in Chapter 3. 28 1.4 Entrepreneurship During this thesis work, we explored the potential of our device by considering founding a start-up company and participated in a 5-week intensive workshop / competition called the Lean Launch Pad (LLP) program hosted by Entrepreneurship at UBC (e@UBC). We discovered, with direct engagement to potential influencers and end-users, how a device like ours can benefit the SCI populations and healthcare clinics. 1.4.1 Customer Segment From the many interviews conducted (>30) with SCI individuals and healthcare professionals, it is clear that there is a great need for a device that is much more affordable than current PMTs and that can perform accurately over long measurement periods. Collecting and obtaining more data leads to more confident diagnosis and analysis, with historical data providing valuable insights to each patient’s daily distribution patterns. 29 1.4.2 Competitive Landscape The oft-used saying “Prevention is better than cure” is the motivation of many, leading to a competitive landscape in PU prevention. At Vancouver General Hospital (VGH) and GF Strong Rehabilitation Centre, XSENSOR [60] and Vista Medical [61] products (PMTs) are used for assessment and educational purposes, but not prevention, as they are expensive and not designed for long-term use in wheelchairs. There are many more companies worldwide trying to enter the market with their sensing technology, cushion [47], [62], or other methods [63], with many being start-up companies. In Table 3, some established and start-up companies are listed with their specific product aimed to relieve pressure and/or aid in the prevention of pressure ulcer formation. This table provides an overview on the current competition and how our sensor compares to them. As this list includes cushions and PMTs, some criteria are “not applicable”. 30 Table 3: Competitive landscape of products focusing on pressure relief and PU prevention in wheelchairs Source UBC Vista Medical XSENSOR Tekscan Sensimat Roho Aquila Product Name N/A BodiTrak2 Pro FortSite SS LX100 BPMS SensiMat Pressure Relief Cushion APK2 On the Market No Yes Yes Yes No Yes Yes Price $ $$$ $$$ $$$ ? $$ $$$ Sensing Resolution High High High High Low N/A N/A Wireless Yes Yes Yes No Yes N/A N/A Shape Conforming Yes (fully) Yes (not fully) Yes (not fully) Yes (not fully) No N/A N/A Continuous Pressure Monitoring (>8h) Yes No No No ? N/A N/A Pressure Relief No No No No No Yes (inactive) Yes (active) PU Prevention No No No No No No No 31 1.4.3 Market Analysis The global market for pressure ulcer treatment products, which include pressure relief devices, wound care device, etc., is estimated to rise from $7 billion (2018) to $11 billion (2026) [64], [65]. The global market for pressure relief devices was estimated to be $2.5 billion in 2015, with an anticipated rise to $4.1 billion in 2025 [66]. Considering that North America (NA) covers approximately one-quarter of the global market and Canada one-tenth of NA, we can assume the market size in Canada for pressure ulcer treatment products to be ~$275 million (2026), whereas for pressure relief devices to be ~$100 million (2025), as shown in Figure 10. Figure 10: Market size for pressure ulcer treatment product (2026) and market size for pressure relief devices (2025) 32 The true market size for the novel sensor depends on the path adopted. For example, it can be sold as a device to either healthcare professionals or individuals with SCI, allowing them to measure and track pressure accurately throughout the day with an integrated alarm warning them to adjust the patient, or themselves. Another option would be by integrating our sensor with a wheelchair cushion, creating a pressure relief device that is capable of measuring pressure distribution across the seating area. This could potentially be achieved by selling our sensor to cushion manufacturers. In Figure 11, it is shown what the potential market would look like within Canada, at a per-sensor price of $50 per unit to the cushion companies. Taking to account that the majority of people with SCI require a wheelchair cushion, and that there are ~86,000 individuals living with SCI in Canada, this would give us a global market size of ~$172 million (~$4.3 million for Canada). Figure 11: Market size for pressure relief cushion with integrated pressure sensor 33 1.5 Sensor Requirements The aim is to develop a sensing device that can assist with the early detection of PU formation in wheelchair users. As current PMTs are expensive, are not fully shape-conforming and show performance issues during long-term measurements, we strive to make our sensor affordable using low-cost materials for fabrication, soft, flexible, stretchable and robust, while performing consistently over long periods of time with applied pressure. In Table 4, a list of set desired specifications is shown for our sensor. These specifications are comparable to the ones of competitors. Table 4: List of desired sensor specifications Sensing Area 45 cm x 45 cm Number of Sensing Taxels 1024 Spatial Resolution 12.7 mm Pressure Range 0 to 200 mmHg Pressure Resolution 5 mmHg Creep ±5% 𝐹𝑆 @ 1h Hysteresis <10% FS Non-Linearity Error 3% 𝐹𝑆 Repeatability 3% 𝐹𝑆 Signal-to-Noise Ratio (SNR) >20 dB 34 1.6 Thesis Objectives & Challenges In the work described in this thesis, the objective is to design and test a sensor that meets the requirements listed in Table 4, and that can also be inexpensive enough to be widely used. The steps involved in meeting these objectives were to: 1. Design and fabricate flexible and stretchable electrode materials that have sufficient electrical conductivity for our application. 2. Design sensor architecture and determine material of use, enabling long-term exposure to pressure and providing accurate readings. 3. Design the fabrication process of the sensor, enabling scaling-up in size. 4. Determine the performance of the sensing device using a variety of physical loads to simulate body weight and determine the robustness of the sensor array. 5. Design a data processing algorithm and alert system. 6. Develop pressure mapping software that visualizes sensing data on Android and iOS platforms. 7. Scale-up the sensor array size. 35 The challenges that we face for this application are as follows: • There are over 200 PU risk-factors, making each case unique [67]. Initially, our device will be set to address pressure only (main risk factor) and to follow the pressure-time curves shown in literature. • The pressure-time curves provided by Reswick & Rogers and Linder-Ganz et al. are the most common ones but still entail uncertainties. For “prevention”, our alert system will adapt to these pressure-time curves, which generalizes our sensor with a more precautionary approach to PU prevention. Further advancements in PU research – potentially made possible by our sensor – will provide a more accurate system, adaptable to each unique case. This may involve adding shear, moisture and temperature measurements. 36 1.7 Thesis Outline This thesis covers the fabrication and analysis of a multi-layered soft, flexible and stretchable pressure sensor, made of low-cost materials, for the potential use of pressure measurements and prevention of pressure ulcers in wheelchair users. This thesis includes four chapters, including this introductory one. The outline for the following chapters are as follows: • Chapter 1 – (Introduction & Background): Defines the motivation of this research work and provides an overview on pressure ulcers and technologies. • Chapter 2 – (Materials & Methods): Describes the materials and methods chosen for fabrication of the pressure sensor, the working principle of the technology, and explains the basic assessment algorithm and alert system. • Chapter 3 – (Results & Discussion): Presents the experimental discoveries of the flexible and stretchable electrodes, and the pressure sensor (4 x 4, 16 x 16), and discusses the results, scalability and potential of the sensor. • Chapter 4 – (Conclusion & Future Work): Summarizes the discoveries, draws conclusions about the sensor performance and 37 the contributions made, defines limitations of the work, and introduces future directions to be continued for this research work. 38 Chapter 2: Materials & Methods 2.1 Introduction A pressure ulcer is a special kind of wound that can disrupt a person’s life completely. It is therefore crucial to find a solution that can help with the prevention of pressure ulcer formation. One of the most promising methods for pressure ulcer prevention is the adaptation of sensors to measure physical stimuli. With the challenges associated with the development of pressure ulcers, it is essential for sensing devices, such as pressure mapping technology (PMT), to be able to measure pressure accurately over long periods of time while being actively deformed by external forces (e.g. pressure) and contours (wheelchair support cushions). For this reason, it is important for such a device to demonstrate sufficient flexibility and stretchability to conform around contours and provide accurate readings. In this thesis, we are investigating the concept and application of a multi-layered soft, flexible and stretchable capacitive based pressure sensor fabricated with low-cost materials that can be placed over wheelchair cushions and potentially scaled up to cover hospital beds. The main objective of our sensor is to measure pressure regions accurately over long periods of time, providing information for diagnostic, educational, research, and prevention purposes. In this chapter, we explain the working principle of our pressure sensor and describe how to produce cEcoflex and fabricate the sensor with soft materials (Ecoflex, PDMS, cEcoflex) in a simple lab environment. The fabrication process in this thesis was deliberately designed to adapt to various sizes of sensors. We also present the circuit board which was designed and developed 39 by the Molecular Mechatronics Laboratory, prior to the beginning of this research work. An expanded circuit board was developed, during the time of this thesis, to accompany the read-out of larger sensor versions with the capability of wireless transmission. Lastly, we discuss the algorithm which processes the data received by the circuitry and delivers the desired pressure readings to the end user, as well as an initial alert system for pressure ulcer prevention (PUP). In Figure 12, the overall system structure is shown, with its implementation and abstraction layers. Figure 12: Block diagrams showing the abstraction layers and the implementation of the overall system for the pressure sensor 40 2.2 Working Principle In this thesis, we have developed a flexible and stretchable pressure sensor that is capable of detecting and measuring pressure using changes in capacitance. To understand the working principle of the sensor, imagine a simple parallel plate capacitor, which consists of two electrodes that are separated by a dielectric layer, as illustrated in Figure 13. The electric field lines in a capacitor pass through the dielectric membrane from the positive to the negative charged electrode, either perpendicularly or with an “edge effect”, with those electric field lines known as fringe fields. When we approach the sensor, which in this case is a capacitor, our body forms a third electrode, as we behave like a virtual ground, and de-couple part of the electric field (mainly fringe fields) between the capacitor electrodes, which reduces the charge and decreases the capacitance overall (Figure 14 - A). This means that any grounded conductor is able to “steal” electric field lines from the capacitor by getting closer to it, which leads to the detection and measure of proximity and light touch. This phenomenon is known as mutual capacitance and is used for applications such as touch screens on laptops, tablets and smartphones. However, our main application does not focus on the detection of proximity or touch but rather on pressure. To measure this physical stimulus, the principle of overlap capacitance is considered. When applying a pressure to the sensor, we are deforming its geometric structure. Visually represented in Figure 14 - B, upon the applied pressure, the two electrodes are getting pushed closer together, which increases the capacitance (C) as the distance (d) between the electrodes is getting smaller and is inversely proportional to the capacitance, according to Equation 2-1: 41 𝐶 =𝜖𝑟𝜖0𝐴𝑑 . (2 – 1) Depending on how the sensor is designed and what materials are used, the area (A) and absolute permittivity of the dielectric of the sensor will have minimal change during deformation and thereby limited effect on the change in capacitance (𝛥𝐶). We can relate the change in capacitance upon applied pressure or compression strain under force loading almost entirely to the change in displacement (𝛥𝑑). An electromechanical model of the sensor discusses this relationship further, below. In the case of in-plane strain, i.e. stretching the sensor, we are not only decreasing the distance (d) but also increasing the area (A), as shown in Figure 14 - C. This results in an increase in capacitance. For our primary application, which is to place the sensor array over a wheelchair cushion, our initial testing suggests that in-plane strain is small and so is not a factor of concern. I neglect in-plane strain effects, as would arise when a person is sitting down, in my deformation-capacitance model. To accurately distinguish and measure the change in capacitance that is solely caused by applied pressure, it is necessary to isolate it, i.e. discard proximity and light touch. This is achieved by shielding the sensor with an added grounded conducting layer, which is further mentioned later in this chapter (Section 2.3). This layer acts as the third electrode that “steals” away the electric field lines from the capacitor. As it is adhered to the surface of the sensor, it will not vary in distance, and therefore does not change the capacitance reading. This provides the capacitance with a new baseline. Any objects that approach the sensor will have no effect on the readings, unless pressure is applied. 42 Figure 14: Working principle of pressure sensor (A) External object (grounded) de-coupling sensor electrodes reducing the capacitance (B) Applied pressure increasing capacitance due to reduced dielectric thickness (C) Applied strain force deforming geometric structure of capacitor resulting to an increase in capacitance. Adapted from Sarwar [57] Figure 13: Parallel plate capacitor with electric field representation including visualization of fringe fields 43 In order to understand the relationship between the change in capacitance (𝛥𝐶), dielectric membrane stiffness (E), and compression strain (𝜖𝑠) under force loading, we start with a simplified representation of a parallel plate capacitor with an elastic dielectric membrane material. The change in capacitance is defined by Equation 2-2: Δ𝐶 =𝜕𝐶𝜕𝐴Δ𝐴 +𝜕𝐶𝜕𝑑Δ𝑑 +𝜕𝐶𝜕𝜖Δ𝜖. (2 − 2) We assume that the area (A) of the capacitor plates and the absolute permittivity of the dielectric (𝜖) are unaffected by the compression. Taking this into account, the change in capacitance can be expressed with Equation 2-3, |Δ𝐶| = −𝜖𝐴𝑑2Δ𝑑 =𝜖𝐴𝑑𝜖𝑠 = 𝐶𝜎𝐸, (2 − 3) where the compression strain (𝜖𝑠) can be displayed as stress (𝜎) over the dielectric membrane stiffness (E). The sensor in this thesis does not behave like an elastic element but rather a viscoelastic one, which is shown in Section 3.2. To describe the viscoelastic deformation of polymers, a four-element model or Burgers model is used, which combines the Maxwell and Kelvin-Voigt models in series, as shown in Figure 15 [68]. This model exhibits all the key features of viscoelasticity, as displayed in Figure 16 [68], and can be expressed by the sum of strains from each component (Equation 2-4): 44 𝜖𝐵𝑀(𝑡) =𝜎𝐸𝑚+𝜎𝑡𝜂𝑚+𝜎𝐸𝑣(1 − 𝑒−𝐸𝑣𝑡𝜂𝑣 ), (2 − 4) where 𝜂 is the coefficient of viscosity. Assuming as before that the area and the absolute permittivity of the dielectric remain unaffected by compression, the relationship between the change in capacitance, dielectric membrane stiffness, and compression strain can be expressed as follows (Equation 2-5): |Δ𝐶| =𝜖𝐴𝑑∗ (𝜎𝐸𝑚+𝜎𝑡𝜂𝑚+𝜎𝐸𝑣(1 − 𝑒−𝐸𝑣𝑡𝜂𝑣 )). (2 − 5) This model shows the generally observed characteristics of a viscoelastic material when stress is imposed. This means that our sensor undergoes an instantaneous elastic strain (𝜎𝐸𝑚), followed by creep (𝜎𝑡𝜂𝑚) and spring limited creep (the last term). Upon the removal of the stress, the sensor experiences another instantaneous elastic strain (𝜎𝐸𝑚), followed by a delayed recovery (𝜎𝐸𝑣(1 − 𝑒−𝐸𝑣𝑡𝜂𝑣 )) and non-recoverable deformation (𝜎𝑡𝜂𝑚). In Chapter 3, the performance results of our sensor and design are shown, where we investigated the ability of the sensor to predict the pressure applied from the change in capacitance. 45 Figure 16: Strain-time behaviour of the Burgers model Copyright © Introduction to Nanofiber Materials, Ko [68]; reproduced with permission of The Licensor through PLSclear. Figure 15: The four-element Burgers model Copyright © Introduction to Nanofiber Materials, Ko [68]; reproduced with permission of The Licensor through PLSclear. 46 2.3 Materials For the purpose of our application, it is desirable that our sensor is able to accommodate to various contours of wheelchair cushions while providing an additional padding layer for comfort and to further delay the formation of pressure sores. To achieve this requirement, the materials need to have the properties of being soft, flexible and stretchable. In addition, to maintain an affordable outlook in fabrication, the materials were chosen to be low-in-cost. For the electrodes, we opted to use ‘cEcoflex’, which is inspired by the advancements in electronic skin [69], [70]. We chose cEcoflex over cPDMS as it is more stretchable, quicker to fabricate and forms a stronger bond with the layers of the sensor. In cEcoflex, carbon black (H30253 Carbon Black Super P® Conductive, 99+%, Alfa Aesar by Thermo Fisher Scientific) and Ecoflex ™ (00-30) were selected for fabrication, as they are readily available in bulk, affordable and easy to use. Ecoflex ™ is a safe material with skin-like feel that has been used in many applications such as facial masks [71]. Carbon black is commonly used as a reinforcing filler in tires and other rubber objects for colour pigmentation and material stiffening [72]. By mixing carbon black particles with Ecoflex ™ 00-30, we produce a conductive elastic material that we refer to as cEcoflex. This combination of properties is needed for the electrodes of our capacitive sensor, so that measurements can be made while still enabling conformability. In Section 2.4.1, we present and discuss the results from various compositions of cEcoflex and determine the approach of fabrication most desirable for our application and environment. In Figure 17, the main sensor architecture is shown, which consists of three layers, two base layers and one dielectric layer. The dielectric layer is made out of Ecoflex ™ 00-30, while the two base layers are made out of a combination of silicones, Ecoflex ™ 00-30 and Sylgard ™ 47 184 (PDMS). This mix of polymers was devised to alter the surface characteristics of Ecoflex ™, making it less sticky, and to enable improved pressure transfer to the dielectric structure for increased pressure sensitivity due to modification of its Young’s modulus. Both materials are stretchable by nature but have different elastic moduli (0.125 MPa Ecoflex ™ 00-30 [73], [74], and 1.3 – 3.0 MPa Sylgard ™ 184 PDMS [75]). A medical grade fabric (Shieldex ® MedTex P70 + B), which is thin, stretchable and conductive, is used to cover and shield the sensor. The shielding layer is not shown in the figure – it sits on top. Figure 17: Cross sectional view of main sensor architecture 48 2.4 Fabrication 2.4.1 Electrodes For a sensing device to measure data accurately over various contours (e.g. wheelchair cushions), the sensor should be shape conforming in order to capture the entire target area. A thin conformable material may not be ideal since there can be unwanted overlap (wrinkles) that could be sources of measurement error and even of increased pressure – causing ulcer formation. This means that a sensor and its electrodes should have the mechanical properties allowing it to bend and stretch, but ideally not wrinkle. How to relate bend and stretch to these aspects is unclear, and needs testing. It will be performed in a subsequent phase of the work. In the meantime, the focus is on using materials and designs that show promise in meeting these requirements. We conducted experiments testing various combinations with different concentrations of carbon black particles mixed in Ecoflex ™ 00-30. Tradeoffs are between stiffness / stretchability / ease of application vs. conductivity, with increased conductivity corresponding to higher carbon black concentration. We observed that the resistance varies quite significantly with the choice of materials and fabrication process. This is important as this sets a limitation for dimensional scaling, due to the RC time constant. The larger the resistance, the longer it takes to charge the capacitive sensor, and so the slower the measurement time. The results are presented and further discussed in Section 2.4.1.1. The scalability of the sensor is discussed in Section 3.5. By scalability, I mean ability to fabricate the sensor array arbitrarily larger, which is constrained by the tradeoffs between measurement rate, size, and number of sensing points. 49 2.4.1.1 Electrical Conductivity The following tests and experiments were conducted to determine the electrical properties of cEcoflex. In the early stages of this work, we determined which concentration of carbon black mixed with Ecoflex ™ 00-30 would provide us with an appropriate balance of conductivity and viscosity for fabrication. The experiments were done with cEcoflex mixtures of 7 wt.%, 13 wt.%, 15 wt.%, and 18 wt.%. Electrode strips were patterned across a large PDMS layer using the doctor blading technique and a hand-cut plastic shadow mask. The doctor blade technique, also known as tape casting, is a widely used precision coating method for producing thin films on large surface areas [76]. By placing the cEcoflex mixture on a shadow mask covered substrate (PDMS) and using a glass slide (the “doctor blade”) to carefully spread the mixture across the area by hand, the electrodes are formed. The electrodes were 24 cm long, 0.25 cm wide and 100 - 300 µm thick. In order to test the conductivity of the electrodes, we connected a power supply to each end of the electrodes with alligator (crocodile) clips and passed a fixed current of 10 µA through them. Copper tape is used as an interconnect to bridge and make contact between the power supply clips and the electrode. This set-up can be seen in Figure 18. 50 We performed a 4-point probe test, where we measured with a multimeter the voltage drop across 5 lengths along the electrode strip (1 cm, 5 cm, 10 cm, 15 cm, 20 cm). With the voltage measurement, we calculated the resistance (R) with Ohm’s Law (Equation 2-6), 𝑅 =𝑉𝐼 , (2 – 6) where V is the voltage and I the current, and determined the conductivity (𝜎) according to Equation 2-7, 𝜎 =1𝜌=𝐿𝑅𝐴 . (2 – 7) Here L is the length and A the cross-sectional area (width x height) of the electrode. Figure 18: Conductivity experiment set-up where a power supply is connected at each end of the cEcoflex electrode with crocodile clips and copper tape. A fixed current of 10 µA is applied and voltage drop is measured. A ruler is used to determine the distances measured by the multimeter 51 In Figure 19, a visual representation of the conductivity results is shown, where we took the average of 10 measurements for each concentration. From the results, we observed that the conductivity of cEcoflex increases with the percentage of added carbon black, with the 18 wt.% solution having a conductivity close to 160 S/m. This was expected as carbon black is the conductive material. However, with a larger amount of carbon black, the consistency of cEcoflex becomes more solid. The 18 wt.% mixture was difficult to doctor blade, as it contained many solid lumps. This might have been reduced by using a motorized mixer instead of mixing the solution by hand, which was at the time the only option. The 7 wt.% mixture had a far more preferable consistency, which allowed for an easier and cleaner process of patterning, with a conductivity of ~10 S/m. We decided to proceed with the 7 wt.% concentration, as a reasonable compromise between conductivity and manufacturability. 52 We realized that the above results are an approximation at best, as there are many uncertainties with the hand-cut mask, mixture fabrication and copper tape strips. At the time, this was sufficient enough to guide us. However, as we progressed, we eliminated as many factors of uncertainty as possible by re-designing the overall layout, having the cEcoflex electrodes connected directly to the power supply (and read-out circuit), and using laser-cut shadow masks for more consistent electrodes (structure and dimensional size). Figure 19: Conductivity of cEcoflex with varying wt.% of carbon black in Ecoflex 53 2.4.1.2 cEcoflex Fabrication Process From the results described above in Section 2.4.1.1, we determined that the appropriate mixture of carbon black particles and Ecoflex ™ 00-30 for doctor blading is 7 wt.%. With this concentration, we were able to doctor blade (Figure 22-1B) smooth electrode strips with a shadow mask, as seen in Figure 20, and achieve reasonable electrical conductivity for initial purposes. Our procedure for making cEcoflex consists firstly of adding part 1A of Ecoflex ™ 00-30 (1A:1B) together with 7 wt.% of carbon black for the entire blend mixture and mixing it for 10 seconds. Next, we add part 1B of the elastomer and mix the complete blend well for 5 minutes by hand. Once thoroughly mixed, it becomes a black paste. 54 Figure 20: cEcoflex electrode strips patterned on base layer post doctor blading process 55 2.4.2 Pressure Sensor The fabrication process for our pressure sensor can be simplified into three main steps: molding, patterning, and bonding, as shown in Figure 21. Figure 21: Simplified fabrication process of the sensor broken down into three main steps: (A) Molding (B) Patterning (C) Bonding 56 The first step consists of preparing the elastomer layers of the sensor. For the base layers, we mix Ecoflex ™ 00-30 with PDMS (Sylgard ™ 184), in a 7:3 weight ratio. This combination of silicones is mixed thoroughly by hand for 5 minutes. Once properly mixed, it is poured evenly into two machined aluminium molds with the dimensions of 120 mm x 57.5 mm x 1 mm. The dielectric layer is prepared similarly, but only with Ecoflex ™ 00-30. The rubber solution, mixed well for 5 minutes by hand, is poured into a custom designed aluminium mold with inverted cylindrical pillars (Figure 21-A). The pillars have a diameter of 3 mm, pitch of 4 mm (center-to-center), and a height of 1.5 mm. Before placing the molds into the oven for curing at 60°C for 1-hour, visible air bubbles that occurred during the mixing process are removed using a syringe needle. All molds have been designed in SolidWorks and machined at The University of British Columbia. The second step is the patterning process (Figure 21-B), where we perform the doctor blade technique, also known as tape casting, for producing thin films over the base layers with a shadow mask. These films are our electrodes, which are made out of a mixture of carbon black particles and Ecoflex ™ 00-30. The blend comprises of 7% wt. of carbon black in Ecoflex ™ 00-30 (1A:1B). This concentration was experimentally chosen after conducting tests shown in Section 2.4.1.1. Our procedure for making cEcoflex is described in the previous section (Section 2.4.1.2). A custom designed mylar shadow mask (PERMEL - Burnaby, B.C., Canada) with a thickness of 0.254 mm is placed over the fully cured base layer. With a glass slide, we carefully perform the doctor blading technique (Figure 22-1B) to pattern the base layers with the rectangular cEcoflex electrode strips that are 2.75 mm wide, 0.254 mm thick, and have a pitch of 12 mm (center-to-center). The mask is later delicately removed and the base layers with the electrodes are left standing at room temperature for 30 minutes. During this time, we prepare 57 another batch of Ecoflex ™ 00-30, which we use to evenly spread over the base layers, and now cured electrodes, with a squeegee to level the uneven parts caused by the patterning process. We leave one end of the electrodes exposed (Figure 22-3B) to provide the read-out circuit board a direct connection to the sensor through alligator clips (Figure 23). Finally, the base layers are once more placed in the oven at 60°C for 1 hour to cure. The third step is the bonding process (Figure 21-C), where we bond together the main three sensor layers and an additional shielding layer (Shieldex ® MedTex P70 + B). The first bond is created by applying an evenly thin adhesive layer of uncured Ecoflex ™ 00-30 over the first base layer with a squeegee and the electrodes facing up, and carefully aligning the base of the recently peeled off dielectric layer to it. Air bubbles that develop during the alignment process will be removed by gently pressing them towards the edge of the sensor by hand. This bond is completed after placing the two layers in the oven at 60°C for 1 hour. The second bond is done similarly but with aligning the cylindrical pillars to the second base layer, so that the electrodes are lined up perpendicularly forming intersections (sensing taxels) of rows and columns. All layers are made to align perfectly with each other, so that each electrode strip is covered by a row of cylindrical pillars (Figure 24). Each sensing taxel has a cylindrical pillar as its dielectric. Once more, this bond is cured at 60°C for 1 hour. The final step is bonding the shielding layer, which covers the sensor surface. The same process is carried out as before. Once completed, the sensor is left at room temperature for 4 hours to achieve its final state. 58 Figure 22: Detailed fabrication process of the sensor. (1A) Customized aluminium molds for base and dielectric layers. (2A) Uncured elastomer mixture poured into molds. (3A) Cured base and dielectric layers. (1B) Patterning cEcoflex electrodes with doctor blade technique using shadow mask (yellow). (2B) Patterned electrodes on base layer. (3B) Leveling surface area. (1C) Adhesive layer applied for bonding dielectric layer. (2C) Bonded dielectric layer. (3C) Bond second base layer. (4C) Small pressure sensor without shielding. (5C) Final pressure sensor with shielding. 59 Figure 24: Cylindrical pillars aligning with cEcoflex electrode strips. This image shows an older version of the dielectric layer (cylindrical pillars with 3 mm diameter, 6 mm pitch). The current design aligns with the electrode strips but provides more pillars, increasing the overall stiffness of the pressure sensor (cylindrical pillars with 3 mm diameter, 4 mm pitch) Figure 23: Alligator (crocodile) clip attached to exposed cEcoflex electrode creating sensor-to-readout circuit board connection 60 The aforementioned process of fabrication was mainly used for making the small sensor (16 sensing taxels). Still, it was designed to accommodate the fabrication of larger sensors as well. However, this process can be optimized, especially when scaling up. With larger molds and a more efficient way of patterning the electrodes, the fabrication time of one sensor can be shortened, significantly. We explored alternative patterning techniques such as screen printing, spray coating, and roll-to-roll, which allow for greater efficiency of fabrication, but involve more expensive set-ups and equipment. These methods also typically require relatively low viscosity of the conductive ink, making it necessary to adapt to each technique, and affecting electrical and mechanical properties. Therefore, due to the resources required and the simplicity of the doctor blading technique, it remained the preferred patterning method in this thesis. For future work, a deeper investigation of optimizing fabrication process for scaling up is encouraged. 61 2.5 Electronics To make use of our pressure sensor, we require a read-out circuit that can interpret the data received and translate them into the desired information for our understanding. In this thesis, we used for the majority of experiments a circuit board that has been designed and developed by the Molecular Mechatronics Laboratory, prior to this research work. This read-out circuit, as seen in (Figure 25-A), consists of one AD7746 capacitance-to-digital converter (CDC), two MAX4518 multiplexers, and an ATmega 2560 microcontroller (Arduino Mega 2560). The CDC is used to measure and convert the capacitance data which is read through the serial interface by the microcontroller. These data are subsequently transmitted via the serial port to the computer. The multiplexers, controlled by the microcontroller, are used to cycle through the sensor arrays, which consist of four rows and columns. For the small sensor, which has a 4 x 4 electrode matrix structure, this circuit can sample all 16 sensing taxels three times a second. This correlates to a sampling frequency of ~ 45.3 Hz. Figure 25-B, shows a simplified function block diagram of this circuit. 62 Figure 25: (A) Read-out circuit board used for the small 4 x 4 sensors, showing flat alligator (crocodile) clips, multiplexers (MAX4518), CDC (AD7746), and microcontroller (ATmega2560) (B) Function block diagram of the read-out circuit. Adapted from Sarwar [57] 63 To accommodate larger sensors, a new circuit board was created, as shown in Figure 26-A. This circuit board features one AD7746 CDC, two ADG731BRUZ multiplexers, a DSD Tech HC-06 wireless Bluetooth serial transceiver, and a STM32 microcontroller, keeping the main architecture the same as the 4 x 4 read-out board. The primary usage of this circuit is to test the basic application of the pressure sensor when scaled up. It is able to measure capacitance from up to 1024 sensing taxels, which correlates to a sensor with a 32 x 32 sensing grid. With insulation-displacement contact (IDC) connectors and flat alligator clips, the sensor and the circuit are connected to each other (Figure 26-B). Figure 26: (A) Read-out circuit board for the 32 x 32 sensors, showing STM32 microcontroller, ADG731BRUZ multiplexers, and AD7746 CDC; (B) Read-out circuit board connected to a non-shielded 16 x 16 electrode grid pressure sensor. 64 2.6 Algorithm As explained in previous sections, our sensor is capacitive based. This means that when our sensor is being deformed by an applied pressure, we see a change in capacitance that relates to that physical stimulus. This data is measured with the read-out circuit and processed by our software algorithm presenting the user with the desired pressure readings. In Figure 27, a flowchart of the algorithm is visually represented. At the start, the Bluetooth layer component operates by continually looking for a data stream, prefixed with a sequence agreed upon by the mobile software and device firmware. Once such a sequence is received, the Bluetooth layer will parse the data stream to check for validity and size. If the packet is valid and of the size expected, the parsed and now packaged data is send to the render component. The render component checks local memory for a look-up table (LUT) of baseline capacitances for each individual sensing taxel. In the case where there does not exist such a LUT, or is deemed outdated, the initial measurement sequence will look to establish that said capacitance baseline. The render component then calculates the difference in capacitance from the baseline, which is converted to pressure in mmHg. This relationship was experimentally determined (Chapter 3) and programmed into the software. To mitigate the noise in the sensor and read-out circuit, a moving average filter is applied to the received sensor data, where the number of frames and weights are programmable within the software. The operation is done by default when the readouts are saved to local memory. 65 Figure 27: Flowchart describing the operation of the algorithm in assessing and storing data 66 2.7 Alert System for Pressure Ulcer Prevention For PUP, an initial alert system was designed to accommodate the basic criteria. In Figure 28, the system overview is shown in a flowchart. The patient-facing mobile application provides a graphical interface to view pressure distribution across the sheet (pressure heatmap). The software identifies locales sustaining high pressures for sufficient durations to be of concern, using the Reswick and Rogers Pressure-Time Curve (Figure 1) [40]. To accommodate the inaccuracies at the extremities, the Linder-Ganz et al. sigmoid function is used [41]. The criterion to trigger the warning alarm further considers physiological factors that the clinician can input to a data acquisition program controlled by LabVIEW. Factors such as the age, weight, systemic blood pressure, nutrition and mobility levels of the patient are considered to further tune the thresholds for which the alarm initiates. When triggered, the host device will make an audible alarm, as well as record the conditions for which the alarm was triggered. In addition to long-term pressure exposures, high impact pressures sustained at the same locations over time are counted and can trigger the alarm as well. This threshold can be set by the healthcare professionals. 67 Figure 28: Alert system overview 68 2.8 Summary & Discussion In this chapter, we described the working principle of our pressure sensor, listed the materials and electronics used, and outlined the fabrication process. In addition, first iterations of our algorithm and alert system were introduced. Our pressure sensor is capacitive based and follows the working principle of mutual and overlap capacitance, being able to detect physical stimuli such as proximity, pressure, and strain. As we are mainly concerned with pressure for our application, we eliminated the detection of proximity by shielding the sensor, allowing for clearer pressure readings. The choice of materials was inspired by previous research, as well as by their low cost and wide availability. One of our main objectives is to keep the fabrication cost of the pressure sensor as low as possible in order to make it affordable and accessible to end users. From our customer segment interviews conducted during our LLP program, we learned that individuals would likely purchase a sensing device as proposed if the cost remained below $300. The fabrication process of the pressure sensor can be summarized into three basic steps listed below: 1. Molding 2. Patterning 3. Bonding The three main sensor layers (one dielectric and two base layers) were made out of elastomer materials (Ecoflex ™ 00-30 and Sylgard ™ 184 (PDMS)) and were molded with custom 69 designed aluminium molds. The electrodes of the pressure sensor are made out of carbon black particles mixed with Ecoflex (7 wt.%), creating cEcoflex. This mixture was patterned on the two base layers with assistance of a shadow mask, which was laser cut, forming the electrode strips. All three layers, plus the shielding layer, were bonded together with Ecoflex, concluding the fabrication process. In this thesis, the majority of the experiments, including characterization of the sensor, were conducted with the 4 x 4 read-out circuit designed by the Molecular Mechatronics Laboratory, prior to this research. This circuit was designed for sensors with 16 sensing taxels, which in our work represents the smaller version. To provide an initial demonstration of the scaling of the sensor, a new wireless read-out circuit was created to accustom sensors up to 1024 sensing taxels. This circuit was primarily used for a larger scale sensor (256 sensing taxel), displaying the pressure readings on a pressure heatmap and testing the algorithm and software application - initial results for which will be presented in Chapter 3. The algorithm and alert system are first iterations, which will be further tuned in the future with more experiments in clinical settings. 70 Chapter 3: Results & Discussion 3.1 Introduction To this day, pressure ulcers remain a significant healthcare concern, despite advances in technology. Current devices, such as pressure mapping systems (PMTs), are promising, yet unaffordable to many. Most systems are thin and flexible but lack in stretchability, which can cause inaccurate readings of pressure in certain areas due to lack of complete conformability and a tendency to wrinkle. These systems are primarily used for short term assessment and education. The majority are not designed to measure pressure over longer periods of time, especially needed for wheelchair use. In this thesis, we are investigating the application of a soft shape conforming pressure sensor that can be implemented as part of an affordable early warning system and aid with the further understanding of pressure ulcers. In this chapter, we demonstrate the performance of a flexible and stretchable multi-layered capacitive based sensor (4 x 4 electrode grid) with its capability to accurately measure pressure continuously over many hours (>12h), within the minimum desired pressure range (0 – 200 mmHg) with good repeatability (0.5% FS), small non-linearity (0.52% FS), low hysteresis error (0.57% FS), and a signal-to-noise ratio (SNR) of 31.64dB. We discuss the design criteria of the pressure sensor and the “ageing effect” of cEcoflex electrodes, and explore the feasibility of dimensional scaling. With a scaled-up sensor version (16 x 16 electrode grid), the resolution and heatmap of our sensor was visualized. 71 3.2 Design & Architecture The architecture of the pressure sensor consists of three main layers (Figure 17), with cylindrical pillars (3 mm diameter and 4 mm pitch) forming the dielectric layer (Figure 29). The thickness of the sensor is approximately 5 mm with all soft layers (shielding, base, and dielectric) bonded together (Figure 30). It was deliberately fashioned to form an additional support layer for the users, further delaying the process of pressure ulcer formation. Figure 29: Dielectric architecture - Cylindrical Pillars 72 Figure 30: Cross-sectional view of 4 x 4 pressure sensor whilst being set-up on the Bose ElectroForce. Sensor placed on glass slide and connected to circuit. Indicating the thickness (~5 mm) and showing internal architecture (dielectric) of the sensor. 73 This overall design and materials were chosen after a number of iterations, as described in Appendix A. The cylindrical pillar structure was preferred, as this basic geometric structure is one of the strongest and structurally sound shapes. This is due to the stress being able to disperse throughout the entire structure. With some trial and error, we found that by keeping the pillars separated, we created a sensor architecture that is strong enough to withstand high pressure (>200 mmHg), yet still sensitive enough to detect lower pressure changes (<32 mmHg). Due to the chosen separation distance of the pillars, the elastomer can widen upon compression without interfering with one another, as there is sufficient space, thereby keeping stiffness relatively low, so sensitivity can meet our needs. Figure 31 presents the stress-strain plots of the pressure sensor with cylindrical pillar structure during compression, one with and without the shielding layer (medical fabric). The strain-time behaviour of the sensor - including the shielding layer - is shown in Figure 32, where a pressure of 200 mmHg is applied for more than 12-hours. An initial pressure experiment testing repeatability and accuracy of this architecture is shown in Figure 33. 74 Figure 31: Stress-Strain plots of pressure sensor with cylindrical dielectric structure (A) No medical fabric shielding layer, (B) With medical fabric shielding. Experiment set on Bose ElectroForce applying 10 sinusoidal cycles of load at 0.01 Hz covering desired pressure range (0 – 200 mmHg) 75 Figure 33: Repeatability and accuracy experiment on sensor design Figure 32: Strain-time behaviour of pressure sensor 76 The sensor does not behave as a perfectly linear elastic element, but more of a non-linear viscoelastic material, as mentioned in Chapter 2. This can be seen in the stress-strain curve, which shows strain stiffening. It is observed in Figure 31 that with the addition of the shielding layer, the sensor trends even further towards viscoelasticity as it becomes slightly stiffer and shows subtle characteristics of creep (hysteresis). Using MATLAB, we determined from the plots the effective modulus for the sensor with and without the shielding layer. In Figure 31-A, the elastic modulus is ~ 145 kPa with the beginning being the softest (𝐸𝑏𝑒𝑔 ≅ 81 𝑘𝑃𝑎) and the end being the hardest (𝐸𝑒𝑛𝑑 ≅ 233 𝑘𝑃𝑎) regions. With the shielding layer (Figure 31-B) the modulus is marginally higher at ~ 152 kPa with the beginning being at ~ 86 kPa and the end at ~ 261 kPa. In Figure 32, it is shown that the strain-time behaviour of our sensor shows a response that is qualitatively similar to the Burgers model, shown in Chapter 2 (Figure 16). There is a step-in strain, followed by an exponential looking rise, followed by a steady creep. The viscoelastic nature means that there will be some apparent drift and lack of repeatability seen in the sensor readout, which needs to be quantified or modeled. In this work, we seek to set bounds on these effects, which are included in the sensor uncertainty. In Figure 33, the sensor demonstrates the ability to measure and distinguish between different pressure values, having 32 mmHg set as the minimum pressure value and 200 mmHg as the maximum. From the plot we can observe that creep gets more significant as applied pressure increases. This is further explored below. The sensor also demonstrates a relatively low-repeatability error, making this design architecture preferable. In Section 3.3.1, the performance of this sensor is explored, analyzing creep, repeatability, non-linearity, hysteresis, sensitivity, and accuracy. 77 3.3 Sensor Performance 3.3.1 Pressure Measurements To investigate the performance of the sensor, we used a Bose ElectroForce dynamic mechanical analyzer together with a mounted load cell and a 3D printed indenter to apply different loads to the 4 x 4 sensor, covering the desired pressure range of 0 to 200 mmHg for pressure ulcers. This set-up can be seen in Figure 34. Figure 34: Experimental set-up on Bose ElectroForce with load cell and 3D printed indenter. 4 x 4 pressure sensor is connected to the read-out circuit and shielded 78 A number of experiments were conducted to investigate the sensor’s pressure sensitivity and capability of measuring pressure over extended periods of time, as discussed below. For the experiments shown in Figures 35, 36 and 37, the forces are applied at a rate of 10 N/s. During all experiments, a small initial force was set to ensure proper surface connection between the indenter and sensor prior to measurement (offset). From the results shown in Figure 35, we observed that the sensor manages to distinguish between different pressure values (37.2 fF (ΔC) @ 32 mmHg with 0.23% creep @ 1h, 126.5 fF (ΔC) @ 110 mmHg with 0.67% creep @ 1h, and 223.6 fF (ΔC) @ 200 mmHg with 1% creep @ 1h) with a steady peak-to-peak baseline noise of < 2 fF) and recovers back consistently to the same baseline capacitance (0.61 pF) after one hour of applied pressure. We also observed that creep becomes more evident along with the increase of pressure magnitude, with 200 mmHg experiencing a creep of 1% at 1h of applied pressure. To characterize the creep, we applied the maximum pressure in our desired range (200 mmHg) and measured displacement. This can be seen in Figure 36. The pressure is held at 200 mmHg for 12 hours. We see that there is creep, and that this creep is also evident in the capacitive response. The total change in capacitance from the start of the step to the end is ~18 fF. Given a sensitivity of 1.16 fF/mmHg, which is obtained later in this chapter, this creep corresponds to an apparent drift in capacitance that corresponds to ~ 16 mmHg or an ~ 2.1% change overall. Comparing to the creep seen in Figure 35, where pressure was applied for one-hour rather than twelve, it can be observed that the creep is reaching a saturation point, going from 1% @ 1h to 2.1% at 12h. This indicates that the creep experienced by our sensor outperforms the desired specification set in Chapter 1. 79 In Figure 37, the sensor was exposed to 100 mmHg (2x for 2 hours each) and 200 mmHg (2x for 1 hour each) with the recovery time at 0 mmHg set to 5 minutes. This experiment was designed to show the repeatability and accuracy of the sensor by simulating a situation where a person is being readjusted after long periods of sitting or lying down uninterruptedly. Again, there is mechanical creep evident, which is seen as creep in the capacitance signal. The capacitance signal remained consistent, recovering back to baseline (0.61 pF) almost immediately, varying by <0.47% over the recovery time. The ΔC for each applied pressure was repeatable within < 0.5% of full range (1 mmHg), as assessed on MATLAB by segmenting each pressure change. Figure 35: Sensor performance with varying pressures magnitudes (I) >10-hour experiment applying 32, 110 and 200 mmHg at 10 N/s for 1-hour each with a 3-hour recovery at baseline 80 Figure 37: Sensor performance with varying pressures (III) 8-hour experiment testing long measurements and repeatability with 100 and 200 mmHg Figure 36: Sensor performance with varying pressures magnitudes (II) 12-hours creep and drift experiment at 200 mmHg with slight disturbances in signal is due to lab environment 81 Next, the difference between sensor elements was investigated. From the same experimental data shown in Figure 37, Figure 38 displays the entire matrix grid of the 4 x 4 sensor, highlighting the noticeable capacitance change on the four activated taxels (Taxel 4, 6, 12, 14), compared to the rest. The neighbouring taxels to the four activated ones (nearest to the red square), show similar signals but with approximately 5-times smaller change in capacitance. This behaviour might be explained by mechanical deformation of the sensor when being compressed, where the neighbouring taxels are experiencing a downward pull, changing the distance (d) of the electrode plates of the capacitor, resulting in a change in capacitance. Interestingly, cross-talk is larger left to right than up and down in the figure. This indicated that there may also be undesired capacitive coupling coming from the electronics, due to adjacent columns. As our CDC works on the principle of floating capacitance, this can cause crosstalk. To minimize the electronic effect on the signal, additional work is required to determine the cause of the crosstalk. It may be necessary to modify the circuitry, potentially grounding all passive channels. 82 Figure 38: Capacitance plot of 4 x 4 sensor showing all 16 sensing taxels when actively deforming taxel 4, 6, 12, 14 (red square) during 8-hour experiment 83 To determine the relationship between pressure and change in capacitance, we applied 10 cycles of sinusoidal load stimulus at a frequency of 0.01 Hz and a load of 17.2 N to reach the pressure value of 200 mmHg. It is observed in Figure 39, that ΔC (y-axis) almost has a linear relationship to the applied pressure (x-axis) with a non-linearity error of 0.52%. This was obtained in MATLAB by applying a Best Fit Straight Line (BFSL) to the plot and taking the largest difference. From this plot we also obtained the hysteresis error (0.57% FS), by taking the maximum difference in sensor output. The sensitivity of the sensor was calculated by taking the slope of the BFSL, which resulted in a rate of ~ 1.16 fF/mmHg. Figure 39: ΔC over Pressure hysteresis plot showing the almost linear relationship 84 In this thesis, the accuracy of the sensor was calculated by taking the Root of the Sum Squared (RSS). As there is no defined standard for pressure sensor accuracy, we based our calculation on a standard set by the International Electrotechnical Commission (IEC). IEC 61298-2 states that accuracy must include hysteresis, non-repeatability, and non-linearity but does not specify how they are combined to make up the accuracy [77]. With the obtained values above (non-linearity error = 0.52%, non-repeatability error = 0.5%, hysteresis error = 0.57%), we calculated our accuracy to be 0.92%. However, there are other methods of calculating the accuracy, such as taking the Root of the Mean Squared (RMS) or simply taking the sum of the three factors. Listed below are the three mentioned methods with the obtained accuracy: • 𝑅𝑆𝑆 = √(𝑛𝑜𝑛 − 𝑙𝑖𝑛𝑒𝑎𝑟𝑖𝑡𝑦)2 + (ℎ𝑦𝑠𝑡𝑒𝑟𝑒𝑠𝑖𝑠)2 + (𝑛𝑜𝑛 − 𝑟𝑒𝑝𝑒𝑎𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦)2 = 0.92%, • 𝑅𝑀𝑆 =√(𝑛𝑜𝑛−𝑙𝑖𝑛𝑒𝑎𝑟𝑖𝑡𝑦)2+(ℎ𝑦𝑠𝑡𝑒𝑟𝑒𝑠𝑖𝑠)2+(𝑛𝑜𝑛−𝑟𝑒𝑝𝑒𝑎𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦)23= 0.31%, • 𝑆𝑈𝑀 = (𝑛𝑜𝑛 − 𝑙𝑖𝑛𝑒𝑎𝑟𝑖𝑡𝑦) + (ℎ𝑦𝑠𝑡𝑒𝑟𝑒𝑠𝑖𝑠) + (𝑛𝑜𝑛 − 𝑟𝑒𝑝𝑒𝑎𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦) = 1.59%. We decided to use the RSS calculation. In RSS, each source of uncertainty is assumed to be uncorrelated with the others, meaning that they are all unlikely to add simultaneously. This accuracy can be considered for short-term pressure measurements, as the values obtained for the calculation were during a period of ≤2h. For long-term pressure measurements, the accuracy to consider, can be obtained by looking at the creep value from a twelve-hour pressure exposure at 200 mmHg (2.1%; ~16 mmHg) and representing it as the FS value. This value corresponds to ±4%. 85 Pressure resolution is referred to as the smallest change in pressure that can be detected. In our case, it would be any capacitance change greater than the peak-to-peak noise experienced at 200 mmHg, which is ~2fF. This corresponds to ~1% of the full-scale Δ𝐶, leading to a pressure resolution of ~2 mmHg. 3.3.2 Signal-to-Noise Ratio Signal-to-Noise Ratio (SNR) is a measure comparing the level of a desired signal to the level of the background noise. Based on our pressure experiments, we analyzed and calculated the SNR of our pressure sensor with the 4 x 4 read-out circuit, which is in the worst-case ~ 31.64dB at 32 mmHg (SNR32mmHg) and in the best-case ~ 46.4dB at 200 mmHg (SNR200mmHg). This last ratio also provides us with the dynamic range (DR). Our SNR calculation is given by: 𝑆𝑁𝑅 = 20𝑙𝑜𝑔 ∗ (|𝑆𝑖𝑔𝑛𝑎𝑙||𝑁𝑜𝑖𝑠𝑒|) = 20 log (|𝛥𝐶||𝑀𝐴𝐷𝑛𝑜𝑖𝑠𝑒|) , (3 − 1) where the signal (peak amplitude) is the magnitude of the change in capacitance (Δ𝐶) for a given pressure value, and the noise (peak amplitude) is the magnitude of the Mean-Absolute-Deviation (MAD) of the baseline signal at 0 mmHg. We determined Δ𝐶 by taking the Mean-Absolute-Value (MAV): 𝑀𝐴𝑉 =∑ |𝐶𝑖|𝑛𝑖=1n , (3 − 2) 86 of the capacitance baseline (at 0 mmHg) and the sensor response at 32 mmHg and at 200 mmHg, which corresponds to the worst- and best-case, and took the difference between them: Δ𝐶 = 𝑀𝐴𝑉𝑝𝑟𝑒𝑠𝑠𝑢𝑟𝑒 − 𝑀𝐴𝑉𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 = Δ𝑀𝐴𝑉 . (3 − 3) The noise was determined by taking the MAD of the signal at 0 mmHg (baseline) prior to the step-increase to 200 mmHg, where here the MAV is taken at zero applied pressure: 𝑀𝐴𝐷 =∑ |𝐶𝑖 − 𝑀𝐴𝑉|𝑛𝑖=1𝑛. (3 − 4) The SNR of the pressure sensor might be further enhanced by designing a new custom read-out board, reducing the parasitic capacitance (𝐶𝑝𝑎𝑟𝑎𝑐𝑖𝑡𝑖𝑐) and noise by shortening the traces, and improving the connection from pressure sensor to circuit board, eliminating potential coupling between the connector clips, which reduces noise levels even more. 87 3.4 Further Investigation of cEcoflex 3.4.1 Ageing Effect We noticed that cEcoflex changes in resistance over time, potentially limiting lifespan, as it affects the accuracy of capacitance readings due to the RC time constant. We discovered that the pressure sensor did not perform as well a few weeks post fabrication. Shown in Figure 40, is the plot of readings from a pressure sensor aged ~ 7 weeks. We can see that at baseline (0 mmHg), the capacitance signal is changing and it does not recover back to its original baseline after a sequence of pressure steps of 32 mmHg, 110 mmHg, and 200 mmHg are applied. This is a vast difference in performance compared to the pressure sensor after a few days post fabrication, where the baseline is steady and the repeatability error is low. Figure 40: Performance of an ageing pressure sensor (~ 7 weeks) 88 The following experiments were conducted over many days (min. 14 days) on three main base layer substrates (Ecoflex ™ 00-30, PDMS (Sylgard ™ 184), and a 7:3 ratio mixture of Ecoflex and PDMS), to measure the change in resistance of cEcoflex (7 wt.%) electrodes. These base layer materials were chosen at the time as they satisfied most mechanical criteria of the sensor. The electrodes (0.275 cm wide, 7 cm long and ~100 𝜇m thick) were doctor bladed on the base layers with a laser-cut shadow mask. For each base layer material, two trials were conducted. The first trial left the electrode exposed to air, the second had the electrode encapsulated with a thin layer of the same material as the base layer. In both cases, conductive clips (flat alligator clips) were used to connect to the Keithley 2410 1100V SourceMeter ®, which allows for 4-point (method) measurements. The alligator clips were fixed to each end of the electrodes and in the middle separated by 4 cm, to allow ease of measurement and to reduce error caused by misplacement of multimeter probes (Figure 41). In Figure 42, the 4-point method results are shown. 89 Figure 41: Experimental set-up (4-point method) for measuring resistance change in cEcoflex over three different base layer substrates over time. Two flat alligator clips are placed at the ends of the electrodes, and another two along the strip separated by a fixed separation of 4 cm. The alligator clips are connected to the Keithley source meter for measurement 90 Figure 42: Resistance measurements of cEcoflex electrodes on three different substrates conducted with 4-point method. (A) cEcoflex electrode exposed on Ecoflex substrate. (B) cEcoflex electrode encapsulated with Ecoflex on Ecoflex substrate. (C) cEcoflex electrode exposed on PDMS substrate. (D) cEcoflex electrode encapsulate with PDMS on PDMS substrate. (E) cEcoflex electrode exposed on Ecoflex/PDMS mixture substrate. (F) cEcoflex electrode encapsulated with Ecoflex/PDMS on Ecoflex/PDMS mixture substrate. 91 We observed that electrodes on substrates and with encapsulation made with pure Ecoflex displayed the highest starting resistance (142 kΩ for exposed and 447 kΩ for encapsulated), as well as the largest increase in resistance over time (218% change (~310 kΩ) for exposed and 490% change (~2.19 MΩ) for encapsulated). Inconsistencies between measurements were also the most prominent for the Ecoflex substrate. A possible reason and source of error for this could be the high stretchability of the material, causing unwanted deformations on measurements which could increase or decrease the resistance. Trials using PDMS as a substrate displayed the lowest initial resistance (11.72 kΩ for exposed and 61.8 kΩ for encapsulated), and changed the least in resistance (122.6% change (~14.38 kΩ) for exposed and 19.6% change (~12 kΩ) for encapsulated). The trend in measurements were also much smoother than the Ecoflex tests, which could be due to the increased stiffness that PDMS provides. The 7:3 Ecoflex / PDMS samples performed predictably between the two other samples, being a mixture of the two substrates. That said, the starting resistance was considerably lower than the pure Ecoflex sample, despite the majority of its composition being made from the more elastic substrate (86.3 kΩ for exposed and 131 kΩ for encapsulated). The resistance for this sample was measured across 14 days and showed a change in resistance of 68% (~ 58.7 kΩ) for exposed and 120% (~ 158.3 kΩ) for encapsulated. For all the samples, the encapsulated electrodes always had a greater resistance than the exposed ones and tend to change more significantly over time. Yet, the PDMS sample was the exception in terms of the change in resistance, as the roles were reversed. From these findings, we proceeded to use the 7:3 mixture base layer for our sensor, as it delivers a more desirable stiffness and surface characteristics than the other elastomers, and improves the electrical conductivity of cEcoflex compared to Ecoflex ™. However, with the 92 steady increase of resistance, it indicates that our sensor will have a certain lifespan and that the dimensional scale is set by the resistance due to the RC time constant, discussed in the next section (Section 3.5). We believe that this effect might be caused by photooxidation of Ecoflex [78], as its chemical structure makes it susceptible to UV-induced photodegradation. During the experiments and storage phase between them, our sensor is exposed to UV radiation. This might cause the bond and connection of cEcoflex to degrade, leading to an increase in resistance. A potential solution is to seal the sensor with a coating or additional protective layer, shielding it from light. To fully comprehend this phenomenon, a wider set of experiments is needed. It would also be beneficial to determine whether this ageing effect stabilizes over time. This can be done by extending the measurement period. 93 3.5 Dimensional Scaling For our primary application to measure pressure and detect pressure ulcer formations across greater areas, such as in wheelchairs or beds, it is necessary for our pressure sensor to be scalable. To determine the maximum dimensions of our pressure sensor, it is essential to consider the RC time constant (𝜏) of the most distant sensing taxel, and the slowest refresh rate that is reasonable – or the lowest frequency of detection of the chosen measurement circuit. The longest RC time constant is determined by the product of the capacitance value of a sensor element, and the resistance of the electrodes. This RC time constant is fundamental as it provides us with the time required for a capacitor to charge-up (𝜏 = 63%, 5𝜏 = 99.9%), which is also the upper bound on the excitation frequency and – for a given design - the electrode resistivity. If a sensing taxel is probed at too high of an excitation frequency (𝑓𝑒𝑥𝑐), the capacitor will not fully charge in time as the resistance will dominate, making the capacitance appear lower. This also explains why the increase in resistance with time of the electrodes can be a problem. If the resistivity of the electrodes increases over time, the capacitor will require more time to fully charge, which may exceed the time of the excitation frequency (12𝑓𝑒𝑥𝑐). Assuming that each sensing taxel is addressed sequentially, the time to fully charge the most distant taxel (5𝜏 conservatively) should be less or equal to the “charging time” of the excitation frequency (5𝜏 ≤12𝑓𝑒𝑥𝑐). If this inequality is not held, the measured capacitance will be underestimated, which ultimately leads to inaccurate pressure readings. We estimated the maximum dimension that we can expand our pressure sensor up-to, with the data obtained in previous sections and the given set-up of circuitry, to be approximately 94 26 cm x 26 cm. This estimation of the maximum length of square array, Lmax, is calculated in terms of the maximum resistance, Rmax, the cross-sectional area, A, and the resistivity, 𝜌, as seen below: 𝐿𝑚𝑎𝑥 =𝑅𝑚𝑎𝑥 ∗ 𝐴𝑒𝑙𝑒𝑐𝑡𝑟𝑜𝑑𝑒2 ∗ 𝜌=(10 ∗ 𝑓𝑒𝑥𝑐 ∗ 𝐶𝑚𝑎𝑥)−1 ∗ 𝐴𝑒𝑙𝑒𝑐𝑡𝑜𝑑𝑒2 ∗ 𝜌=𝐴𝑒𝑙𝑒𝑐𝑡𝑟𝑜𝑑𝑒20 ∗ 𝜌 ∗ 𝑓𝑒𝑥𝑐 ∗ 𝐶𝑚𝑎𝑥. (3 − 5) The maximum resistance value (Rmax) can be expressed as the dividend of the time constant, 𝜏, and the Mean-Absolute-Value (MAV) capacitance of the most distant sensing taxel at 200 mmHg pressure (~0.83 pF), 𝐶𝑚𝑎𝑥. The worst-case resistivity value of cEcoflex (𝜌 ≅ 1.99 Ω ∗ 𝑚 @ Day 14) was obtained from Figure 42-F, where the excitation frequency, 𝑓𝑒𝑥𝑐, was obtained from the CDC (32 kHz). Depending on the chosen application for the pressure sensor, the refresh time (T) and the number of sensing taxels (n) can be specified. It is important to note that the sampling time of a single sensing taxel (𝑇𝑛) must be ideally greater than or equal to 5𝜏. To increase the dimensions of our pressure sensor, and to exceed the estimated dimensions of 26 cm x 26 cm, we can either modify the circuitry (↓ 𝑓𝑒𝑥𝑐), change the capacitor dimensions to lower the baseline capacitance (↓ Area (width x height), ↑ separation distance (d)), increase the cross-sectional area of the cEcoflex electrodes to reduce the resistance (↑ thickness, ↑ width) and/or increase the conductivity of the electrode by switching to an alternate material. As we want to keep the main architecture of the pressure sensor, it is suggested to explore alternate materials for the electrodes that have better conductivity and similar mechanical properties to cEcoflex and do not increase in resistance over time, and to re-design the circuitry 95 with more suitable components (CDC and MUXs) to accommodate larger sensors. Even though cEcoflex showed promise for our application, we have been investigating the use of conductive fabric as a substitute and potentially transforming our pressure sensor into a fabric based one that can be implemented as a wearable device. This can be seen in the future work section in Chapter 4. 3.6 Resolution & Pressure Heatmap Visualization As a first step in scaling, we fabricated a medium size sensor (16 x 16 sensing taxels), keeping the design and materials the same as for the small sensor (4 x 4 array grid), and characterized it accordingly. To perform initial tests of the sensor array, we created a pressure heatmap with colour gradients to display the pressure readings. We placed the medium pressure sensor on a flat table connected to the circuit board with wireless transmission and simulated a potential real-life application where a person sits on the sensor. Once the subject was sitting on the sensor, the pressure data was processed and displayed on the pressure heatmap, as shown in Figure 43. The red regions indicate high pressure, whereas the green regions are low. In Figure 44, we show the pressure distribution and outline of an applied force to the pressure sensor with a flat hand. This test was conducted to determine that the spatial resolution of the pressure sensor is sufficient to outline smaller pressure areas that can be caused by ischial tuberosities, heels, etc. As these prone location areas vary in size based on the individual, they are similar or even smaller than fingers. We observed that the sensor is capable of measuring pressure and can distinguish between different pressure magnitudes. This being displayed on the pressure heatmap. The spatial resolution (12 mm) is shown to be 96 sufficient, outlining smaller pressure areas, such as fingers, distinctly. It is comparable in spatial resolution to commercial devices, including from XSENSOR and Vista Medical, which have a spatial resolution of 12.7 mm [60], [61]. Figure 43: Characterized medium size pressure sensor being tested with the pressure heatmap on smart phone. Pressure heatmap indicating where there is high pressure (red) and low pressure (green) regions on the subject while sitting on a hard-flat surface 97 Figure 44: Testing the resolution of the medium size pressure sensor (16 x 16 sensing grid). Pressure sensor is placed on a rigid surface and connected to the read-out circuit. A force is applied with a flat hand with the pressure heatmap on the right outlining the shape of the hand and indicating the pressure magnitudes experience by each sensing taxel 98 3.7 Summary & Discussion The pressure sensor presented in this chapter is soft, flexible, and stretchable with non-linear viscoelastic properties. Its elastic modulus during compression is ~ 152 kPa on average cross the entire operating range (0-200 mmHg), with modulus at small strains (< 5%) reaching ~ 86 kPa and at large strains (> 15%) ~ 261 kPa. The pressure sensor demonstrated its ability to detect and distinguish pressure accurately and consistently in the desired pressure range for short- and long-term use with a low repeatability error (< 0.5% FS, <1 mmHg), creep (1% change (~7 mmHg) over 1 hour at 200 mmHg, 2.1% change (~16 mmHg) over 12 hours at 200 mmHg), hysteresis (0.57% FS), non-linearity (0.52%), and accuracy (0.92%). These performance results are satisfactory and show potential in applications for pressure ulcer detection, research, and ultimately prevention. Table 5 highlights the obtained results from this chapter. In addition, by using low-cost materials, our pressure sensor can challenge current devices on the market, which are significantly more expensive and perform comparably - in some cases even worse - than our sensor. In Chapter 4, we compare the specifications set in Chapter 1, which are inspired by devices from competitors, with the specifications from our sensor. 99 Table 5: List of specification obtained by our sensor Pressure Range 0 to 200 mmHg Pressure Resolution 2 mmHg Creep < 3% 𝐹𝑆 @ 12h Hysteresis 0.57% FS Non-Linearity Error 0.52% 𝐹𝑆 Repeatability 0.5% 𝐹𝑆 Signal-to-Noise Ratio (SNR) 31.6 dB Dynamic Range (DR) 46.4 dB Sensitivity 1.16 fF/mmHg Accuracy ±0.92% (short-term measurements) ±4% (long-term measurements) 100 For the flexible and stretchable electrodes, it came to our attention that our pressure readings over time did not perform as well as they did at the very beginning post-fabrication. This led to further investigation into the cEcoflex electrodes. With a controlled experiment, we tested the cEcoflex material with three different substrates (Ecoflex, PDMS, and 7:3 ratio mixture of Ecoflex and PDMS) and measured the resistance with the 4-point method over several days. We observed that cEcoflex behaves quite differently when applied on different elastomer substrates. On Ecoflex, the resistance of cEcoflex showed the highest starting resistance, as well as the largest increase in resistance over time. On PDMS, it displayed the lowest initial resistance and smallest change. The mixed substrate of Ecoflex and PDMS performed in-between the two aforementioned materials, which provided overall the best characteristics and properties for our pressure sensor. The conductivity of cEcoflex on 7:3 Ecoflex / PDMS substrate started off at ~ 1.11 S/m, which is more than adequate to scale up the pressure sensor dimensions to ~ 58 cm x 58 cm, but decreased after 14 days to ~ 0.50 S/m. This indicates that our pressure sensor with the cEcoflex electrodes has a lifespan. Regarding the SNR and DR, our pressure sensor, together with the 4 x 4 read-out circuit, has an SNR of ~31.6 dB and a DR of ~46.4 dB, which indicates a good signal transmission, providing accurate pressure readings. To further enhance the sensitivity of the pressure sensor, next steps may include a re-designing of the read-out circuit board, and sensor-to-circuit connection improvement, reducing noise even more. For our initial application to make an affordable pressure sensing mat for SCI individuals in wheelchairs and for healthcare professionals working in wound care settings, our pressure sensor would require to be scaled up to a minimum dimension of 45 cm x 45 cm to cover a standard wheelchair seat for an average adult. With our current pressure sensor using cEcoflex 101 this can be achieved by setting its lifespan to 5-days and making it disposable. However, this is not considering the shelf-life. Further work and testing is required to understand this “Ageing Effect”. Based on some literature findings, a potential solution might be to cover it from UV radiation, as exposure degrades the Ecoflex material. This needs to be further investigated. Alternatively, the simplest approach to improve the pressure sensor’s lifespan would be to use a different material for the electrodes with a better and more stable electrical conductivity, and similar mechanical properties (flexible and stretchable) to cEcoflex, while keeping the main sensor architecture the same. A material such as silver-plated knitted fabric (Shieldex ® MedTex P70 + B) is one of many alternatives for the sensor electrodes. In addition, a protective layer will need to be applied to shield the sensor from unwanted moisture and bodily fluids, making it cleanable and re-usable. Ecoflex and PDMS being hydrophobic by nature, can be considered, as well as a stretchable waterproof fabric, such as polyurethane. Further test will have to be conducted for characterization with the additional protection layer and electrode material. In theory, our pressure sensor can be used for assessment, education (pressure ulcer research and patient education) and justification purposes, in addition to being a first iteration prevention device. For wheelchair users, the sensor can be placed over the support cushion and used throughout the day. The pressure data will be collected, stored, and processed based on our sensor characterization and algorithm. The data can be re-called and viewed in a pressure heatmap representing the pressure distribution at selected times. The end users have the ability to share their data with their healthcare professionals, which provides more detail for diagnostics. The initial alert system identifies locales sustaining high pressure for significant durations, as well as high pressure impacts sustained over time on the same regions. The criteria to trigger the warning alarm is based on the Reswick and Rogers pressure-time curve and the sigmoid injury 102 threshold, and the criteria set by the clinicians. This system and algorithm can be further fine-tuned for each unique case with the additional physiological factors that can be input by the healthcare professionals, such as age, weight, systemic blood pressure, nutrition, and mobility levels. When triggered, the host device will make an audible alarm as well as record the conditions for which the alarm was triggered. Future clinical experiments and further consultations with our clinical advisors are required to successfully establish and finalize the aforementioned performance features, which may lead to a product launch. Next steps are to fabricate the larger molds and sensors to the minimum dimension of a standard wheelchair seat, improve the read-out circuit board and sensor-to-circuit connection, and conduct clinical experiments with able-bodied and SCI individuals. Success will provide the healthcare system with a device that is affordable, soft, flexible, and stretchable, that can be used to measure pressure over long periods of time, aid as an educational and assessment tool for healthcare professionals in wound care or as a research tool for academics, and ultimately as a pressure ulcer prevention device. In Chapter 4, we discuss potential directions and new implementations of this research work. This discussion includes exploration of the use of silver coated nylon yarn as an electrode alternative using the same working principle, with the intention of moving closer towards wearable textile-based sensors, which can be used for patients in the intensive care units (ICU), as well as SCI individuals. 103 Chapter 4: Conclusion & Future Work 4.1 Conclusion In this thesis, we proposed a pressure sensing device that can accurately measure pressure continuously over hours and help with the prevention of pressure ulcers in wheelchair users. We presented a soft, flexible, and stretchable multi-layered sensor made out of low-cost materials, that can detect a range of different physical stimuli with the main emphasis on pressure detection. We demonstrated that our pressure sensor can measure pressure over short- and long periods of time with good accuracy and repeatably, some creep and at a reasonable resolution for the proposed application, with the results displayed on a pressure heatmap. Table 6 below, is a comparison of desired specifications, listed in Chapter 1, which are based off devices on the market, and our obtained specifications in Chapter 3. We were able meet almost all the desired specifications, except the sensing area and the number of sensing taxels. This was due to limitations in mold fabrication and oven size. However, all other specifications were met and even exceeded. This indicates that our sensor is suited for our desired applications and has the potential to rival current pressure mapping devices on the market, in performance and cost. 104 Table 6: Comparison table of desired and obtained specifications Desired Specifications Obtained Specifications Sensing Area 45 cm x 45 cm ~ 4 cm x 4 cm (small sensor) ~16 cm x 16 cm (medium sensor) ~ 32 cm x 32 cm (large sensor) Number of Sensing Taxels 1024 16 (small) 256 (medium) 1024 (large) Spatial Resolution 12.7 mm 12 mm Pressure Range 0 to 200 mmHg 0 to 200 mmHg Pressure Resolution 5 mmHg 2 mmHg Creep ±5% 𝐹𝑆 @ 1h < 3% 𝐹𝑆 @ 12h Hysteresis <10% FS 0.57% FS Non-Linearity Error 3% 𝐹𝑆 0.52% 𝐹𝑆 Repeatability 3% 𝐹𝑆 0.5% 𝐹𝑆 Signal-to-Noise Ratio (SNR) >20 dB 31.6 dB Dynamic Range (DR) - 46.4 dB Sensitivity - 1.16 fF/mmHg Accuracy - ±0.92% (short-term measurements) ±4% (long-term measurements) 105 Future work in this specific direction, includes scaling up the sensor to a standard wheelchair seat size, advancing the electronics (reducing noise, suitable for large scale sensors, and wireless transmission) and electrodes (testing cEcoflex and alternative materials), conducting clinical experiments, and fine-tuning the algorithm and alert system in consultation with our clinical advisory group. In addition, further advancement of the sensor is recommended such as the integration of shear and moisture detection to touch upon other extrinsic factors of pressure ulcer development. 4.2 Limitations Fabrication: The fabrication process of our sensor was designed to accommodate a range of sensor sizes. When scaling up the sensor, we were limited to the medium size version, as we did not have a large enough oven at the time for a potentially larger mold. Characterization: For most of the experiments on the Bose ElectroForce dynamic mechanical analyzer, we were limited to testing the smaller sensor version and up to a maximum of four sensing taxels at a time due to the set-up of the Bose, as well as the load cells on hand. 106 4.3 Future Directions This pressure sensor presented above shows promise in tackling the challenges of pressure ulcer prevention. In this thesis, the main motivation was to develop an affordable sensing mat that covers a wheelchair seat and can measure pressure accurately for daily usage. However, there are many other directions where this technology can be used. In terms of pressure ulcers, future directions may include but are not limited to: Smart Bedsheet: Scaling up the pressure sensor to cover segments or the entire area of standardized hospital and nursing home beds, capable of measuring pressure, shear, temperature, and recognizing position. Autonomous Prevention Device for Wheelchairs: Using the shape conforming pressure sensor presented together with a secondary pressure relieving device (mechanical actuation), such as a pneumatic cushion, to create a fully autonomous product for pressure ulcer prevention. This would avoid the need for the user to respond, or for a care-giver to intervene. The pressure sensor acting as the “skin” sends signals to the secondary device “muscle”, relieving at-risk areas of pressure when needed without unnecessarily moving the user which can cause new potential risk areas due to shear and friction. Prosthetic: Using the soft characteristics and ability for accurate pressure readings over short- and long-term periods of this sensor can be useful for lower limb prosthetic users, as they form a so-called stump ulcer. The amount of pressure accumulating over the small areas is significantly higher than 200 mmHg, potentially reaching up to >1,000 mmHg, which means further characterization of the sensor is required, and possibly re-design. Resolution and size of the sensor can be adapted to accommodate desired applications. 107 Diabetic Foot Ulcer: Developing an in-sole or sock using the soft sensor, providing additional cushioning and ability to measure pressure around the foot while walking. This device can track with the pressure readings abnormalities in a person’s gait, indicating a lack of sensation, which can lead to pressure ulcers. Smart Clothing & Wearables: Incorporating sensors inside clothing, measuring vital signs, is an upcoming field and attracting great interests from experts in the fields of sports, healthcare, wellness, and fashion. For pressure ulcer prevention, it would be beneficial to have garments that are stretchable and include soft pressure sensors as it would eliminate measurement errors caused by external layers, as well as allow continuous monitoring throughout the day. In collaboration with Saki Tamura from the Department of Advanced Fibro-Science at the Kyoto Institute of Technology, Japan, we explored the use of textile within our pressure sensor, venturing closer to fabric-based sensors that can be potentially integrated in clothing. We presented our work “Woven Structure for Flexible Capacitive Pressure Sensors” at the annual Material Research Society (MRS) conference and published in MRS Advances [79]. We investigated the use of an alternate electrode material (Ag yarn) and a woven electrode structure. Using the same principle of the pressure sensor shown in this thesis, we fabricated soft sensors, using Ecoflex ™ 00-30 as the dielectric, and silver coated nylon yarn as the electrodes Figure 45. This work shows the first iteration of the pressure sensor using fabric-based electrodes. Further research is required to optimize and develop a sensor that can be integrated in clothing for at-risk individuals. [57] 108 This work has shown the potential of this soft, flexible and stretchable sensor. Future work will be required to further advance this sensing device, potentially launching it to market. 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Designs with extruded crosses, loops, bubbles, cylindrical pillar, etc., were created to modify the stiffness of the sensor, allowing it to become more sensitive to external pressure compared to a pure elastomer layer acting as the dielectric. All the designs were tested with the Bose ElectroForce. Below are three iterations shown, along with additional performance results. Figure 46 shows the first iteration of the chosen cylindrical pillar design in this thesis, showing promising results in pressure detection, repeatability, and creep. This result inspired us to continue modifying this structure to finally obtain the design used in this work. Figure 47 shows a design iteration using loops, as we also referred to as “Life Savers”. This design did not perform well, showing a significant amount of creep and low sensitivity to pressure. Potential reason for this result is the effect of the air bubble that forms when bonding the elastomer layers. Figure 48, is a combination of loops and cylindrical pillars. This design performed better than the pure “Life Savers” one, but still showed undesirable characteristics including creep and repeatability. The reason for this, again, might be due to the air bubbles within the loops. 120 Figure 47: Hollow cylindrical pillars "Life Savers" design and performance plot Figure 46: Cylindrical pillar design and performance plot 121 Figure 48: Cylindrical pillars and "Life Saver" combinations design and performance plot
Thesis/Dissertation
eng
Biomedical Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
A soft flexible and stretchable pressure sensor array designed to warn of pressure ulcer formation
Text