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BMC Neurology. 2020 Nov 18;20(1):419
The Author(s)
AlMahadin, Ghayth
Lotfi, Ahmad
Zysk, Eva
Siena, Francesco L
Carthy, Marie M
Breedon, Philip
Background: Parkinson’s disease is the second most common long-term chronic, progressive, neurodegenerative disease, affecting more than 10 million people worldwide. There has been a rising interest in wearable devices for evaluation of movement disorder diseases such as Parkinson’s disease due to the limitations in current clinic assessment methods such as Unified Parkinson’s Disease Rating Scale (UPDRS) and the Hoehn and Yahr (HY) scale. However, there are only a few commercial wearable devices available, which, in addition, have had very limited adoption and implementation. This inconsistency may be due to a lack of users’ perspectives in terms of device design and implementation. This study aims to identify the perspectives of healthcare professionals and patients linked to current assessment methods and to identify preferences, and requirements of wearable devices. Methods: This was a qualitative study using semi-structured interviews followed by focus groups. Transcripts from sessions were analysed using an inductive thematic approach. Results: It was noted that the well-known assessment process such as Unified Parkinson’s Disease Rating Scale (UPDRS) was not used routinely in clinics since it is time consuming, subjective, inaccurate, infrequent and dependent on patients’ memories. Participants suggested that objective assessment methods are needed to increase the chance of effective treatment. The participants’ perspectives were positive toward using wearable devices, particularly if they were involved in early design stages. Patients emphasized that the devices should be comfortable, but they did not have any concerns regarding device visibility or data privacy transmitted over the internet when it comes to their health. In terms of wearing a monitor, the preferable part of the body for all participants was the wrist. Healthcare professionals stated a need for an economical solution that is easy to interpret. Some design aspects identified by patients included clasps, material choice, and form factor. Conclusion: The study concluded that current assessment methods are limited. Patients’ and healthcare professionals’ involvement in wearable devices design process has a pivotal role in terms of ultimate user acceptance. This includes the provision of additional functions to the wearable device, such as fall detection and medication reminders, which could be attractive features for patients.
AlMahadin et al. BMC Neurology (2020) 20:419 https://doi.org/10.1186/s12883-020-01996-7RESEARCH ARTICLE Open AccessParkinson’s disease: current assessmentmethods and wearable devices forevaluation of movement disorder motorsymptoms - a patient and healthcareprofessional perspectiveGhayth AlMahadin1, Ahmad Lotfi1, Eva Zysk2, Francesco Luke Siena3, Marie Mc Carthy4 andPhilip Breedon1*AbstractBackground: Parkinson’s disease is the second most common long-term chronic, progressive, neurodegenerativedisease, affecting more than 10 million people worldwide. There has been a rising interest in wearable devices forevaluation of movement disorder diseases such as Parkinson’s disease due to the limitations in current clinicassessment methods such as Unified Parkinson’s Disease Rating Scale (UPDRS) and the Hoehn and Yahr (HY) scale.However, there are only a few commercial wearable devices available, which, in addition, have had very limitedadoption and implementation. This inconsistency may be due to a lack of users’ perspectives in terms of devicedesign and implementation. This study aims to identify the perspectives of healthcare professionals and patientslinked to current assessment methods and to identify preferences, and requirements of wearable devices.Methods: This was a qualitative study using semi-structured interviews followed by focus groups. Transcripts fromsessions were analysed using an inductive thematic approach.Results: It was noted that the well-known assessment process such as Unified Parkinson’s Disease Rating Scale(UPDRS) was not used routinely in clinics since it is time consuming, subjective, inaccurate, infrequent and dependenton patients’ memories. Participants suggested that objective assessment methods are needed to increase the chanceof effective treatment. The participants’ perspectives were positive toward using wearable devices, particularly if theywere involved in early design stages. Patients emphasized that the devices should be comfortable, but they did nothave any concerns regarding device visibility or data privacy transmitted over the internet when it comes to theirhealth. In terms of wearing a monitor, the preferable part of the body for all participants was the wrist. Healthcare(Continued on next page)*Correspondence: philip.breedon@ntu.ac.uk1School of Science and Technology, Nottingham Trent University, Clifton Lane,NG11 8NS Nottingham, UKFull list of author information is available at the end of the article© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriatecredit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes weremade. The images or other third party material in this article are included in the article’s Creative Commons licence, unlessindicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and yourintended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directlyfrom the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The CreativeCommons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data madeavailable in this article, unless otherwise stated in a credit line to the data.AlMahadin et al. BMC Neurology (2020) 20:419 Page 2 of 13(Continued from previous page)professionals stated a need for an economical solution that is easy to interpret. Some design aspects identified bypatients included clasps, material choice, and form factor.Conclusion: The study concluded that current assessment methods are limited. Patients’ and healthcareprofessionals’ involvement in wearable devices design process has a pivotal role in terms of ultimate user acceptance.This includes the provision of additional functions to the wearable device, such as fall detection and medicationreminders, which could be attractive features for patients.Keywords: Parkinson’s disease, Focus groups, Interviews, Healthcare professionals, Patients, Wearable devices,Qualitative analysis, PreferencesBackgroundParkinson’s Disease (PD) is the second most commonlong-term chronic, progressive, neurodegenerative dis-ease. It mainly affects the motor system, and the cardinalmotor symptoms are rest tremor, bradykinesia, rigidity,and postural instability [1–3].PD prevalence varies from 41 people per 100,000 in thefourth decade of life to over 1900 people per 100,000 inpeople over 80 years of age [1]. According to the Parkin-son’s Foundation [4], more than 10 million people world-wide are living with PD, and about one million people inthe United States (US) alone. The annual estimated directand indirect cost of PD in the US is $52 billion [4]. Inthe United Kingdom, the estimated number in 2018 wasaround 145,000; that is approximately one adult in every350 [5].PD is linked with morbidity, mortality, high economicburden, and a decreased quality of life. However, studiesshow that positive results can be achieved in the man-agement of motor symptoms in the early stages. Theconsequences of late or incorrect diagnosis have a neg-ative impact on individuals’ patients and health servicesystem [6–8].Clinical rating scales are essential to quantify neurolog-ical disorders symptoms, impairment and disability [9].Clinical rating scales in PD enable researchers and clini-cians to evaluate disease symptoms, severity, progression,treatment efficiency, response and side effects as well aspatients and their caregiver [9–11]. Several clinical ratingscales have been developed since the 1960s. The PD ratingscales can be categorised into impairment scales, disabil-ity scales and multi-modular scales (impairment scalesand disability scales) [10]. The most commonly used rat-ing scales of PD motor symptoms are: Hoehn and Yahr(HY) [12] and Unified Parkinson’s Disease Rating Scale(UPDRS) [13].Hoehn and Yahr (HY) scale was designed originallyin 1967 to estimate the disease severity combining defi-ciency and disability based on bilateral motor involvementand compromised balance and gait [14]. It is a simplescale describes the stage of PD from 1 to 5 based onmotor impairment severity and disability. The HY scalehas been used widely and has universal acceptance as ascale to describe PD stages due to it is simplicity and abil-ity to group PD patients based on motor and functionalityseverity and progress [15]. The main advantage of the HYscale is its ease of use, but it is a classification scale andnot a rank order [16], i.e., the stage does not reflect thedisability as someone in stage 2 may be more impaired foractivities of daily living (ADL) than someone in stage 3.The Unified Parkinson’s Disease Rating Scale (UPDRS)was published in 1987 and become the most widelyused rating scale [11]. However, the UPDRS scale hassome ambiguities and limitations. The Movement Disor-der Society (MDS) has identified some of the limitations,including ambiguities in questions, poor instructions andthe absence of important aspects of non-motor symp-toms. Their findings have led to revised version MDS-UPDRS to resolve identified problems in the UPDRS andto enable better detection of small changes and milddisabilities [13]. MDS-UPDRS consists of 65 elementsrequires 30 min administration time distributed amongfour parts; I) Non-motor experiences of daily living (13elements), II) Motor experiences of daily living (13 ele-ments), III) Motor examination (33 elements), IV) Motorcomplications (6 elements) [13]. Each element scoredfrom 0 to 4 where (0: normal, 1: slight, 2: mild, 3: moder-ate, and 4: severe), some elements are self-administratedby patients without any help, and some elements are com-pleted with or without help from a caregiver, but indepen-dently from the examiner, and some elements are rated bythe examiner based on observation and physical examina-tion. The MDS-UPDRS scale designed to avoid medicalterms to be easier for PD patients, and it applies to PDpatients with different levels of disabilities [9].Even thoughMDS-UPDRS assessment is internationallyaccepted rating scale to assess PD, and enhanced the qual-ity of clinical trials outcomes, and has undergone strictclinimetrics validation, but it is clinically based scale, thatthe clinician assigns numerical scores based on qualita-tive observations of the patient in various postures andare often insensitive and subjective, so, the assessmentAlMahadin et al. BMC Neurology (2020) 20:419 Page 3 of 13depends on the examiners’ skills and knowledge, and itis various from one examiner to another, so examiners’disagreement on assessment and scores [17–19]. Thereis evidence showed that MDS-UPDRS has high inter andintra-rater variability between nurses’ and neurologists’assessments [20–22]. Thus, a patient’s tremor may beassigned MDS-UPDRS score by one examiner and in thenext appointment assessed by a different examiner andassigned a higher score. In this situation, it is difficult tointerpret these two different scores, whether symptomsworsen or due to subjectivity.TheMDS-UPDRS scale is time-consuming and requireslengthy administration time, approximately 30 minutes,besides it requires specialised official training to improvethe coherence of data acquisition and interpretation, thesemake it unhandy for routine clinical practice [13, 23].Another time burden thatmany elements inMDS-UPDRSneed to be completed by patients, so additional time isrequired besides the time required to review these ele-ments by the examiner. This time burden limits the use ofthe MDS-UPDRS in routine clinical practice. Therefore,MDS-UPDRS scale is mainly used in clinical research. Theassessment performed in a clinical environment does notmirror day to day symptoms, which might vary during theday or the last few weeks or months and can only cap-ture a snapshot of patient’s symptoms at thatmoment [15].Moreover, many elements of the MDS-UPDRS scale donot apply to each patient, so these questions may raiseanxiety in patients, consequently influence their assess-ment, besides incompetent usage of examiner’s time.Additionally, many elements in MDS-UPDRS scaledepends on patients memory, which is unreliable and lim-ited by recall bias [17–19] due to that fact that mostpatients are elderly, they exhibit cognition and demen-tia issues. PD can also cause cognitive dysfunction evenin early stages which affect patients recall capabilities[24, 25]. Also, long time between appointments makesit difficult to remember symptoms during this period,besides it is an inconvenience for patients to travelto the clinic due to the weather conditions, trans-portation, distance, and their conditions, particularlyin advanced stages of the disease [26]. Therefore, anearly objective and more detailed, accurate, and reli-able diagnosis and assessment could be a contribut-ing factor to help increase the chance of effectivetreatment. This could decrease disability over time,thus cutting down on direct and indirect healthcarecosts [3, 27].Wearable technologies have been increasingly intro-duced for more accurate motor assessment. They haveshown promising results in research and clinical trials toobjectively measure and monitor symptoms, both on-siteand remotely [18, 28–32]. However, a limited number ofcommercial systems are available for such purposes [33]such as SENSE-PARK system,1 Kinesia system,2 Parkin-son’s Kinetigraph (PKG)3 and Physilog,4 and where theydo exist, they show limited adoption and implementa-tion [34] despite of the fact that these devices shows highreliability, validity and responsiveness [33, 35], and havebeen used in the evaluation of PD symptoms and signsby individuals apart from development team and reportedsuccessful clinical trials [35, 36]. Data from several studiessuggest that these inconsistencies in adoption and imple-mentation may be due to the lack of users’ perspectives indevices design and development [37, 38].Even though users’ preferences need to be considered ifwearable devices are to gain acceptance at home or withina clinic [39, 40], a recent systematic review shows that theresearch to date has tended to focus on wearable devicesdevelopment from quantitative perspectives such as typeof sensors, data extraction, and classification methods.There is little attention paid to users’ preferences withfew studies reporting patients’ or clinicians’ experiences,preferences, and expectations of using wearable devices[31]. here is evidence that remote and continuous moni-toring plays a crucial role in treatment quality of patients,as well as reducing costs that afflict the healthcare sys-tems by reducing hospitalizations and increasing patients’satisfaction.In addition, remote and continuous monitor-ing makes it possible for physicians to identify diseaseand its progression early in life and to track changes overtime [41], for example, a study conducted by New EnglandHealthcare Institute (NEHI) demonstrated that remotemonitoring resulted in a 60% reduction in hospital re-admissions in England with estimated annual saving of upto £6.4 billion [42].High-quality medical devices with high levels ofpatients’ and healthcare professionals’ acceptancerequires engineering methods such as user-centereddesign (UCD) philosophy [37, 43] that places an empha-sis on patients’ and healthcare professionals’ individualneeds as well the environment where the devices willbe used. It is suggested that innovations that are oftendriven by technology evolution may increase the ‘risks’that researchers develop products that only a few peopleneed and are willing to use [44]. Product developmentmust also take into consideration users’ involvement inthe early stages of device design and development wherechallenges and possibilities, ideas, and concepts arepresented and discussed, thus minimising costly devicemodifications and reducing recalls. This could lead tomore robust usable devices that are better suited to users’needs [38, 44].1http://www.sense-park.eu/sense-park-system.php2http://glneurotech.com/kinesia/products/kinesia-360/3https://globalkineticscorporation.com/the-pkg-system/4https://gaitup.com/physilog-sensor/AlMahadin et al. BMC Neurology (2020) 20:419 Page 4 of 13A recent systematic literature review was conducted byJohansson et al. [31] found that few studies have exploredpatients’ preferences or healthcare professionals’ prefer-ences or both [23, 39, 45–56]. However, such studiesremain narrow in focus dealing only with device accep-tance rather than users’ needs, and in addition, most ofthese studies have investigated either patients’ perspec-tives or healthcare professionals’ perspectives and havenot included both in the same study. For example, somestudies [23, 46, 53] utilized questionnaires to get feedbackonly from patients linked to existing developed wearabledevices and focusing on user satisfaction, comfort andwearing the device publicly. Also, these studies did notinvolve or explore the design requirements from patients’point of view or from healthcare professionals. Con-versely, some studies explored healthcare professionals’perspectives, for example, Santiago et al. [52] conducteda survey to evaluate the impact of using a commerciallyavailable wearable device (KinetiGraph™ or PKG) in rou-tine clinical appointments of PD patients from physicians’point of view. The study has explored how a developeddevice could add value to current assessment, but it didnot take into consideration the design aspects and whatare the requirements since it is limited by feedback aboutgathered data.Few studies explored the needs and the requirementsof patients and healthcare professionals. For example,Bergmann et al. [39] used an online questionnaire to iden-tify the preferences of medical wearable devices for peopleaffected with arthritis, so these preferences can be usedin devices design and developments. However, this studydid not take into consideration clinicians’ or physiother-apists’ preferences, which ultimately might limit deviceadoption. In addition, arthritis conditions such as jointpain might influence arthritis patients’ preferences; forexample, the preferable part of the body to place the wear-able device, which might be different from other diseasessuch as PD. Similarly, Bruno et al. [45] used an onlinesurvey to identify users’ perspectives toward digital tech-nology and wearable devices, but in this study, people withepilepsy, caregivers, and healthcare professionals wereincluded. However, most of these studies have utilisedquestionnaires, and approaches of this kind carry withthem various well-known limitations [57]. For example,questions understanding and interpretations, the diffi-culty of conveying feelings and emotions, and they are notflexible and do not allow probing to get in-depth informa-tion [58]. In contrast, focus group discussions and inter-views can explore a range of views, perceptions, thoughts,and sentiments and can provide insight into complicatedsubjects [59].Few studies utilized focused group discussions to gainan in-depth insight into patients’ perspectives, and thesecan help to design and develop wearable devices withhigh acceptance and adoption. For example, Papi et al.[50] used focus group discussions to identify designrequirements and mode of use of wearable technology forpatients with osteoarthritis. Similarly, Thilo et al. [54] andXing et al. [55] have used the same approach to identifyelderly people perspectives toward wearable technologies,but, of these only one study has explored PD patients’ andhealthcare professionals’ preferences in-depth, utilizingfocus group discussions [49].Based on an extensive review of the literature andthe subsequent completion of the study, we are ableto present one of the first comprehensive qualitativestudies that has explored both patients’ and health-care professionals’ perspectives. This is specifically linkedto current diagnosis and assessment methods, wear-able devices design and materials, and the require-ments and specification of a combined PD monitoringsolution.Considering the aforementioned limitations, initially,this study employed semi-structured interviews and focusgroup discussions to identify the perspectives of health-care professionals and patients linked to current diagno-sis and assessment methods. It also helped to identifytheir preferences, needs, and requirements of wearabledevices to ultimately assess and monitor symptoms of PD.Secondly, their expectations and outlooks on potentialsolutions.MethodsData collectionA holistic approach was adopted by first using exploratorysemi-structured interviews, and later focus group discus-sions according to the procedure used by Lambert andLoiselle [60]. The first step in this approach was to con-duct four preliminary semi-structured individual inter-views for healthcare professionals interviews topic guide,see Additional File 1); three with healthcare professionals(2 females, 1 male; age range: 52-61 years) were recruitedfrom the Royal Derby Hospital, and one interview with65 years female Parkinson’s local supporter was recruitedfrom Parkinson’s UK, who closely works with PD patientsand is understanding of their needs and requirements indifferent ways such as emotional support, informal dis-cussions about patients worries and experiences. Also,she arranges social events and invites healthcare profes-sional speakers to provide information about PD. Thisvoluntary work enrich her experience and knowledgeabout PD patients’ requirements. These interviews wereutilised to obtain further in-depth information on thecurrent diagnosis and assessment processes. The results(themes) from the exploratory interviews were used togenerate a discussion guide for the patient focus groupsfor patients focus groups topic guide, see Additional File2). The interview with the local supporter was used to linkAlMahadin et al. BMC Neurology (2020) 20:419 Page 5 of 13healthcare professional with patients views and not togenerate themes.The second step was to conduct three focus group dis-cussions involving 12 PD patients (5 females, 7 males; agerange: 56-88 years) were recruited through Parkinson’sUK, each lasting approximately 60 minutes. The discus-sions followed a semi-structured topic guide to allow adeeper insight into product design and development. Thetopic guide was designed to elicit general discussion witha more specific question as probes used if they were notraised or discussed by participants as per the recom-mendations of Braun and Clarke [59]. The demographicinformation of participants is summarised in Table 1.Data analysisAudio recordings of the healthcare professionals’ inter-views and patients’ focus groups were transcribed verba-tim by the lead researcher, which enabled initial familiari-sation with the data. The data was then analysed usingan inductive thematic approach following the six phasesguideline as outlined by Braun and Clarke [59]. Thisinvolved familiarisation with the data by reading tran-scripts multiple times and annotating initial ideas andcoding interesting elements in the data with a systematicapproach by:1 Organising data in meaningful forms.2 Grouping codes based on potential themes.3 Organising data in meaningful forms.4 Grouping codes based on potential themes.5 Collecting data relevant to each theme.6 Reviewing themes by refining themes or sub-themesby splitting, combining themes and find therelationship between themes.7 Defining and writing up the themes.8 Final analysis and connect analysis to the researchquestion.The results from the interviews analysis were utilisedto design a focus group topic guide. Verbatim quotes areindicated using the following notation: I indicates Inter-view, G indicates focus group, F indicates female,M indi-cates Male, and the number indicates the focus group orinterview number. For example, GF1 (Female from focusgroup number one).Results and discussionsThis study investigated patients’ and healthcare profes-sionals’ opinions toward the current diagnosis and assess-ment process together with their preferences towardwearable technology and their expectations and out-looks on potential solutions. Limitations of existing solu-tions and barriers to their use were explored alongsidewearable technology design requirements and expectedsolution outcomes. Both groups of participants showedan unanimously positive response towards the use ofwearable technology for remote continuous monitoring.The results from interviews identified the following rel-evant themes: (1) Current diagnosis and assessment aredubious art, (2) The role of aesthetics and design foracceptance and adoption (3) Patients and healthcare pro-fessionals want wearable technology that eases and refinestreatments.Current diagnosis and assessmentmethods are dubious artA common view amongst interviewees was that thecurrent assessment is subjective, dependent on clinicalexpertise, and thus, inconsistent. Also, there is muchscope for Type I (False Positive) and Type II (False Nega-tive) errors in diagnosis.“The consultation thing can be a little bit subjective.We doubt each other’s assessment.” (IM1)“Sometimes we see patients who have been diagnosedwith Parkinson’s disease, but later it turns out to benot Parkinson’s.” (IF3)”So, it is about listening to their story, making yourown assessment and discussing the options, whichmight help. It is very much an art.” (IF4)The interviews show the need for objective data fordiagnosis and to distinguish between tremor and otherabnormal movements such as essential tremor (ET). Prob-ing questions about the reason behind this suggestedthat it is very difficult to differentiate PD tremor fromET tremor, especially in early disease stages, which isconsistent with other research that has reported a highmisdiagnosis rate of PD and ET to be approximately 25%of cases [61].Table 1 Participants demographic informationData source Gender Male : Female Number of participants Age (year) Mean ± SD(range)PD Duration (year) Mean± SD (range)Focus Group 1 2 : 1 3Focus Group 2 3 : 3 6 73.83 ±10.69 (56 - 88) 8.5 ±7.29 (2 - 24)Focus Group 3 2 : 1 3Interviews 1 : 3 4 57.75 ±6.29 (52-65) NAAlMahadin et al. BMC Neurology (2020) 20:419 Page 6 of 13“[New assessment method] Will be able to tell thedifference between those types of movements. So, youknow, that would be, that will be helpful.” (IM1)The current assessment and monitoring processes aredependent on patients’ memories and diaries which arenot reliable, as previous studies suggested that 30-40% ofPD patients will develop dementia [24], besides the factthat most patients are elderly and several lines of evidencesuggest that memory decline occurs in individuals olderthan 60 years [62]. Also, many PD patients are unawareof their symptoms often cannot distinguish between PDsigns and other abnormal activities [63].“[Patients] Do not always remember precisely . . .they [Neurologists] might see them six months or evenevery 12 months . . . clinically we [Neurologists] askedthem to video the movement that they are talkingabout.” (IM1)This study supports evidence from previous observa-tions that current diagnosis and assessment scales aresubjective, infrequent and depend on clinicians’ skills andpatients’ recall [17, 18, 64].Sometimes consultants ask patients to video tremorsthey are experience at home for assessment, but elderlypatients may often not be familiar with modern technol-ogy such as wearable and social computing as exemplifiedbelow, and also shown by [65].“They do not always know, and a lot of these patientsare elderly, and they maybe get the instructions, or theywill not know how to video.” (IM1)A highly surprising fact that emerged from the datawas that the health care professionals reported scale orscore systems were not commonly used for diagnosis andassessment, including the UPDRS. Probing questionsabout the reason behind this suggested that assessmentscales are time burden and need repetition. This resultmay be explained by the fact that UPDRS is primarilyused for clinical trials and research.“I do not give numbers [scores for the symptoms]they [researchers] might do in a research study.” (IM1)“We do not tend to use UPDRS routinely in theclinic.” (IF4)Late diagnosis was a common concern amongstpatients, due to late referral from general practitioners(GPs), as most GPs were not suspecting Parkinson’s in thefirst visits. However, most of the patients were diagnosedcorrectly and quite quickly when they were examined by aneurologist. Another reported problem was that patientsreported having symptoms years before they went to seea doctor or were referred to a specialist.“A pain in the shoulder, . . . the doctor gave me acoat and an injection. That seemed to ease it, but thenI needed them. I did not do anything about it for amoment. I just left it, and then I noticed that I waswalking, and my right arm was not moving . . . Thenthe doctor told me I had a clot on my brain.” (GM1)“Dr [Name] diagnosed me and provided me a pre-scription for having some form of, what did he call it?spinal plates. ” (GM3)Concerns were expressed about infrequent assessment;the patients reported that assessments were typicallycarried out every six months. In addition, assessmentdepends on a patient’s memory or diary and does not ofteninvolve examination or physical assessment. Instead, itmainly focuses on generic subjective patients reports (e.g.,“how are you?” “have you got any issues?”). Consistentlywith healthcare professionals’ reports, none of the partici-pants mentioned UPDRS motor examination. A commonview amongst patient interviewees was that infrequentassessment affects their treatment by not taking the rightmedication and the right dose due to long-time betweenappointments, and their symptoms might be controlledduring the first few months post-assessment but notfor the entire six months period. However, all patientsreported that they can call nurses between appointmentsif they feel unwell or if they have any issues.The patients, on the whole, demonstrated that theyexperience “peaks and troughs” from hour to hour andfrom day to day, and some of the symptoms appear ata specific time of the day or when they are doing spe-cific tasks; these patterns are not picked up during clinicassessment.“Because I have on and off [Symptoms fluctuation] Ihave started going on and off, so I am m sort of up anddown, up and down. ” (GM1)The role of aesthetics and design for acceptance andadoptionFrom healthcare professionals’ point of view, wearabledevices would be acceptable to most patients, particularlyyoung patients. Device visibility may depend on the stageof the disease; healthcare professionals believed patientsin more complex stages of PD would be more likely will-ing to wear visible devices than would newly diagnosedpatients.“So, it depends on what stage of Parkinson’s you aretalking about. So, if you are going to go to somebodyAlMahadin et al. BMC Neurology (2020) 20:419 Page 7 of 13newly diagnosed, they probably want something prettydiscreet. But somebody who is in the more mainte-nance, more complex phase they may wear somethingthat is a bit more visible.” (IF3)Device design is one of the most important factorsthat determine whether patients are willing to wear thedevice. In line with previous studies [23, 39, 48, 49, 54, 56]healthcare professionals felt that the device must be com-fortable, easy to use, non-invasive, and should easilybe worn under clothes without catching/snagging. Thedevice should also be water-resistant, washable, durable,and easy to fasten to minimise daily disruption.One main objective of this study was to determine themost preferable and suitable part of the body to wearthe device without affecting data quality. All healthcareprofessionals independently suggested the wrist wouldbe most appropriate, with some focusing on reasons ofpatient comfort and others on detection of PD tremorcharacteristics. Given that most typical tremor in PD iscalled a ‘pill-rolling’ rest tremor involving movement ofthe thumb and index finger, the wrist would be an appro-priate location for the device as it could reliably pickup this type of tremor. These viewpoints match thosereported in earlier studies [66, 67].Healthcare professionals were familiar with what wear-able devices are and their use and functionality, and theyshowed awareness of some commercial devices used fordiagnosis and assessment, such as Parkinson’s Kineti-graph (PKG). However, none had ever used these beforebecause they are expensive, and the reports are difficultto interpret. All healthcare professionals reported thatwearable devices that available commercially have mostlybeen used for advanced treatments such as deep brainstimulation and advanced therapies.“It is quite expensive. They do use it, [Neurologist’sname] in [City name] he uses them a bit because he isdoing, um, he has access to very expensive treatmentand so he wants very objective data to give them theexpensive treatment . . . The software that they havedeveloped to interpret the device finding is quite com-plicated” (IM1)”But I think the biggest problem with that is thatyou have to pay a certain amount of money for everyreport. Neurologists at [Hospital name] use it whenthey are thinking about advanced therapies” (IF4)When asked about wearable technology, most patientshave not heard about or used wearable technology. Fol-lowing an explanation of the purposes of this technologyas a part of this study, the majority of patients takingpart in this study stated that they would be willing to usewearable technology and to be monitored 24/7, as long asthe device is not invasive or on an undesired part of body(e.g., neck or ankle). Patients stated the preferred part ofthe body was the wrist, as one would wear a watch; thiswas echoed by every participant in this study. This fur-ther supports healthcare professionals’ point of view. Also,these results are in keeping with previous observationalstudies [66, 67].Issues related to technology such as violation of privacy,difficulty in learning how to use technology, fear anddiscomfort of using technology and lack of human inter-action were not particularly prominent in the discussion.Except for one patient who thought that the fear or dislikeof modern technologies (Techno-phobia) could be abarrier for many elderly people, which echoes healthcareprofessionals’ perspectives. What is interesting about thisresult is the conflicting perspectives between healthcareprofessionals and patients. In addition to the growth inthe number and proportion of older people [68] suggestthat technology acceptance and adoption maybe is notrelated to techno-phobia, but due to different perspec-tives and lack of training on new technologies, in additionto technology designs that do not meet users’ needs andrequirements.“Well, I do not think it is an issue. I mean if it is ifsomebody is going to try it in the first place to see if it isgoing to work for everybody . . . a lot of all the peopledo not trust modern technology” (GM1)Regarding wearable design aspects, there are a numberof similarities between interviews and focus group discus-sions in terms of what patients would want, including forthe device to be comfortable, non-invasive, waterproof,durable, small, and easy to fasten. Patients’ discussionsfocused on the wearable hardware side more than didhealthcare professionals. For example, patients discussedwhich materials are more comfortable, breathable, notsweaty/sticky, soft and spongy, including cloth over metal,leather, neoprene, reinforced material, stainless steel, rub-ber and silicon. Even though they held differing viewsabout what material should be, common ground was touse comfortable material. Moreover, all patients focusedon the device wearing style, which be easy to fasten asthe tremor affects their ability to fasten traditional claspssuch as a buckle or flip styles. Velcro and elasticated strapswere the most preferable styles to patients; for example,it was pointed out that Velcro straps could be tight-ened as needed. Some patients offered it would be betterif they were involved in the development stages of thedevice. These findings are in line with previous studies[23, 39, 48, 49, 54, 56] in which wearable tech-nology’s acceptance was determined by appearance,comfortability, size, and ease of fitting.AlMahadin et al. BMC Neurology (2020) 20:419 Page 8 of 13“What about these plastic, leathery straps becausethis all new stuff coming out. The only thing l wouldlike is a nice easy clasp because that I have got veryfaster on it, because this is my worst hand so if I havetried to do my watch, that is why I have gone facilitylike this [He showed clasp of his watch] that I can wearit easily, something sticks together” (GF3)“I think it might be nice to have an insight into thedevelopment stages of whatever the devices that youare going to use so that we can have some input orwhether you take it onboard or not” (GM1)None of the patients had any concerns about devicevisibility. Perhaps somewhat remarkably, they wantedthe device to identify them as people affected by PD, soit might indicate to the community they may need help.Indeed, It has been shown that psychological supportwould be helpful for people with PD, since emotionsaffect the severity of the symptoms [69]. Also, it helpsthose affected avoid unwanted and uncomfortable situ-ations if people know about their disorder, for example,the public might think they are drunk due to the nature oftheir symptoms. The feeling of embarrassment in publicdue to PD symptoms has also been described in otherstudies of PD [70–72].“If it is designed to do with Parkinson’s and in timepeople got to know if they saw that on you, you gotParkinson’s, he might need help” (GF3)“That happened to me when I was going through thepark. People thought I am the people sitting on a benchthough I was drunk they call back to me, told me totake more water with it, you know, just the usual gobby,which in fact that upset me. I never went out actuallyafter that for a few days because it upset me that much”(GF2)Patients and healthcare professionals want wearabletechnology that eases and refines treatmentsWhen asked healthcare professionals about their expec-tations and outlooks from potentials monitoring andassessment solutions, remarkably all interviewees shednew light on their expectations that the solution couldlead for a better or new treatment, and as discussed in“The role of aesthetics and design for acceptance andadoption” section that objective data is needed for expen-sive treatment as reliable markers; therefore, the solutioncould help improving current treatments or leadingfor new ones. The expected solution could be used toevaluate treatments efficacy in terms of medications andrehabilitation.“If the nurse altered the medication, and you candetect if the medication reduced patient tremor a bitor knew it did not, or the tremor is bit worse, and thatis what you kind of go on, and that is enough, youknow, because then you can either try medication tryrelaxation techniques.” (IF3)There were some suggestions from healthcare profes-sionals that the solution should be easier to use, provide“very concise” information, and be easy to interpret.As mentioned in “The role of aesthetics and design foracceptance and adoption” section, one of the main rea-sons that interviewed healthcare professionals are notusing devices available commercially the complexity ofinterpreting their data and results.“It might be ideal to have something that measuredtremor in some way or whether somebody was havingan off and on, but it just needs to tell us that quicklyand simply, without needing a degree in mastery thecharts” (IF3)”I think the information it would give would need tobe very concise. We would not have time to be goingthrough reams” (IF4)Concerns regarding lack of information of symptomfluctuations were widespread among healthcare profes-sionals, supporting that symptoms fluctuate from time totime during the day and from day to day. Results showhigh interest from healthcare professionals in contin-uous monitoring and its importance in diagnosis andtreatment decisions. This finding reflects evidence fromprevious studies that showed the benefits of continuousmonitoring [41, 73].“Lots of patients come to us with issues at certaintimes of the day, whether it is tremor or slowness andstiffness or fatigue or, or you know, being sleepy or youknow, all of which could be the symptom of Parkinson’s”(IF4)“A pattern to their off time and it might help thenurse how to adjust the medication . . . If you hadsomething [a solution] that was a bit more technicaland a bit more useful in revealing symptoms.” (IF3)Consistent with the literature [32, 41, 74], this researchfound that remote monitoring has a pivotal role in PDtreatment as well as healthcare cost reduction, mainlyfor large geographical areas, and it could help patientswho are not in the vicinity of a hospital to be diagnosed,particularly in cases of severe symptoms that make travelAlMahadin et al. BMC Neurology (2020) 20:419 Page 9 of 13difficult. Also, it is easier and more efficient use of timefor healthcare professionals to assess patients remotelyrather than traveling to their homes.“Who is living way away, they might not be ableto come to the clinic too often. [Neurologist’s name]in[City name] used it [Wearable device name] becauseI think the geographical area that they cover is quitelarge” (IF3)Remote and continuous monitoring was a recurrenttopic throughout the discussions; patients seemed tobelieve it would help clinicians identify their symptomfluctuations and patterns during the day, and if the medi-cation does not help patients to manage their symptoms,continuous monitoring could enable clinicians to changemedication in a timely way. Also, it was suggested to tracksymptom history over a period before a clinic visit, whichwould ensure that clinicians do not miss any informationthat might affect patients’ treatment.“It would be better if it is 24/7 because then you goto get the full picture of the 24 hours, aren’t you? . . .Because it is very tiring if you have got Parkinson’s totravel a long way in a day” (GF1)“I think if that goes through on that and is somethingthe doctor picks up and appointment comes through tosee quite quickly because something in yourmedicationis not working as good as we think it could do.” (GF3)There were some suggestions to other functionalitiesto the device, such as fall detection and medicationreminders, as this information could help healthcareprofessionals and patients alike, as forgetting medicationsand falls are common in PD patients/older age generally[54, 75].“Something that counted falls would be usefulbecause patients do not remember how many falls theyhave . . . Medication reminder would be useful anddoes not stop until they have taken it” (IF3)When asked patients about their expectations andoutlooks from potentials monitoring and assessmentsolutions, a common view amongst patients was thatearly precise diagnosis and accurate frequent assessmentcould make their life easier and lead to better treatment,as mentioned earlier by GF3 and below statement.“Something that could make our life easier” (GM1)“Privacy sort of goes out the window” (GM2) wasthe response if the patients have any concern regardingtransferring the data over the internet or if someonesees their data or PD information, unlike those in earlierresearch [45, 49–51, 55]. The current patients seemed tobe comfortable forgoing their privacy rights in terms ofdata access for the overall benefit of treatment. It was alsofound that patients do not have concerns about devicevisibility. On the contrary, patients made suggestionsthe device should be visible to identify them as peopleaffected PD and that they may need help. This findingcontrasts with previous studies which emphasize patients’preferences for the device to be discreet [39, 45, 50].“I have Parkinson’s. I am not bothered who knows Igot Parkinson’s” (GM1)“Privacy, no, I think you lose all your privacy whenyou have got something like Parkinson’s” (GF2)Supplementing the health care professionals’ interviewsresults, it was suggested by patients to add a medicationreminder option to the wearable devices and the applica-tions as patients report facing issues with rememberingtaking the right medication on time. Additionally, patientsalso suggested a help call button would be useful on thedevice to summon an emergency contact when needed.“I take my medication at set times during the day.Well, this will be able to remind me which medicationto take on time” (GM2)“I am wondering if you can put something on yourwatch and, say, I fall in the house or outside. If a pressthat button it goes straight through to my daughter’sphone and I can speak to her” (GF3)Previous research has established that user accep-tance has a pivotal role in wearable technology adoption[23, 39, 49, 52, 56]; however, very few studies focusedon wearable design methods, particularly the utilisationof user-centered design (UCD) philosophy. The currentstudy offers some key insights into user involvement inearly design stages and to identify patients’ and health-care professionals’ requirements and preferences, and theimportance of patients and medical professional inputwas highlighted by participants in this study. Moreover,the prior disregard of such input (alongside the down-sides of costliness and difficulty of interpretation of com-mercially available devices) may help explain the lack ofcommonplace adoption of wearable technologies. If usersare involved in the design process, the device may bet-ter suit their needs and overcome any barriers to theiruse. Some options important to users may have previ-ously been neglected by designers, such as medicationreminders and fall detection, which may further interestAlMahadin et al. BMC Neurology (2020) 20:419 Page 10 of 13patients and healthcare professionals to use such wearabledevices.In summary, these results show that current assessmentand monitoring processes are subjective and depend onclinicians’ skills and experiences. It was commented that“the consultation thing can be a little subjective”. Also,they are not routinely applied in clinics because theyare time-consuming and rely on patients recall, as oneinterviewee said: “We do not tend to use UPDRS rou-tinely in the clinic”. The participants’ perceptions aboutusing wearable devices to evaluate symptoms were sup-portive and suggested that this objective evaluation couldmake the current assessment easier and enhance currenttreatment. As one participant reported that “he wantsvery objective data to give them the expensive treatment”.Another important finding was that no concern was raisedabout wearable devices visibility or private data conveyedthrough the internet. For example, one interviewee said“Privacy sort of goes out the window”. Participants wereinterested in participating in device design, and they haveproposed many design aspects and options that increaseuser acceptance and adoption. As one interviewee putit “I think it might be nice to have an insight into thedevelopment stages”.Study limitationsWe acknowledge that this exploratory study has sev-eral limitations. First, The sample size may not be fullyrepresentative of the wider PD and healthcare providerpopulation. Second, all participants were residing in theNottingham area. Hence, perceptions may differ in otherregions of the world which may limit the generalizability.However, qualitative research rarely seeks to generalizebut to explore perceptions. Third,While interviewing par-ticipants, we have noticed different levels of knowledgeand experience with technologies, so responses were likelybased on previous experience with available technolo-gies, such as wearable devices or smartwatches. There-fore, future research should attempt to include partic-ipants from different regions, with different experienceand knowledge.ConclusionIn conclusion, this qualitative study found that currentassessment and diagnosis methods are subjective anddepends on healthcare professionals’ skills, and this maylead to inconsistent assessment. Currently, there is nogeneral agreement about a reliable, valid, sensitive andcost-effective device to assess PD symptoms. Through thisstudy, healthcare professionals’ and patients’ perspectivesof wearable technology were positive and how it couldbe utilised to improve the current assessment process,thus increase the chance of effective treatment. A com-mon view amongst interviewees was that participation inthe design process of wearable devices is a crucial aspectof user acceptance. That involves fitting out additionalfeatures for the wearable device, like fall detection andmedication alerts, which could be appealing to patients.The outcomes from this research can help to design high-quality wearable devices with a high level of patients’ andhealthcare professionals’ acceptance by considering users’requirements and involving them in the design process.Supplementary InformationThe online version contains supplementary material available athttps://doi.org/10.1186/s12883-020-01996-7.Additional file 1: Healthcare Professional Interview Topic Guide. Thisdocument contains the semi-structured interviews guide used withhealthcare professionals.Additional file 2: Patient Focus Group Topic Guide. This documentcontains the semi-structured focus group guide used with patients.AbbreviationsUPDRS: Unified Parkinson’s disease rating scale; HY: Hoehn and Yahr; PD:Parkinson’s disease ADL: Activities of daily living; MDS: Movement disordersociety; PKG: Parkinson’s kinetigraph; NEHI: New England healthcare institute;UCD: User-centered design; JICEC: Joint Inter-College ethics committee; ET:Essential tremor; GPs: General practitionersAcknowledgementsWe would like to thank all participants for their openness and willingness toparticipate in our interviews and focus group discussions. We are thankful toParkinson’s UK and Royal Derby Hospital to their help in recruitment and toPaul Watts for his help in data collection.Authors’ contributionsGA: Conceptualization, methodology, formal analysis, writing - original draft,writing - review and editing, project administration, investigation. AL:Validation, writing - review and editing, supervision. ES: Methodology, writing -review and editing, supervision. FL: writing - review and editing. MM: Writing -review and editing. PB: conceptualization, methodology, resources, writing -review and editing, supervision, project administration, funding acquisition.The author(s) read and approved the final manuscript.Authors’ information• Ghayth AlMahadin is currently PhD student at Nottingham TrentUniversity. He received his BSc in computer engineering from MutahUniversity, MSc in Cloud and Enterprise Computing from NottinghamTrent university. Ghayth research interests include wearabletechnologies, machine learning in medical applications.– Qualification:MSc– Designation: PhD Student– Email: Ghayth.almahadin2016@my.ntu.ac.uk• Ahmad Lotfi is a Professor of Computational Intelligence and Head ofDepartment of Computer Science at Nottingham Trent University, wherehe is also leading Computational Intelligence and Applications researchgroup. His research focuses on the identification of progressive changesin behaviour of elderly people suffering from Dementia or any othercognitive impairments. Accurate identification of progressive changesthrough utilisation of unobtrusive sensor network or robotics platformwill enable carers to intervene when deemed necessary. Researchcollaboration is established with world-leading researchers. He hasworked in collaboration with many healthcare commercial organisationsand end-users including Tunstall Healthcare Group and NottinghamAdult Care. He has received external funding from Innovate UK, EU andindustrial companies to support his research. He has authored andco-authored over 200 scientific papers in the area of computationalintelligence, internet of things, abnormal behaviour recognition andAlMahadin et al. BMC Neurology (2020) 20:419 Page 11 of 13ambient intelligence in highly prestigious journals and internationalconferences.– Qualification: PhD– Designation: Head of Department of Computer Science– Email: ahmad.lotfi@ntu.ac.uk• Eva Zysk is currently lectures in Psychology at the University of BritishColumbia in Vancouver, Canada. Eva Zysk’s research interests lay in theaetiology, phenomenology, assessment and treatment of mentaldisorders, using both quantitative and qualitative approaches. Her mostrecent work involved developing a virtual reality exposure therapy appfor social anxiety disorder.– Qualification: PhD– Designation: Lecturer– Email: evazysk@psych.ubc.ca• Francesco Luke Siena is an award-winning designer and Lecturer inProduct Design. He received his BSc (Hons) in Computer Aided ProductDesign, MSc in Smart Design and PGDip in Professional ResearchPractice at Nottingham Trent University and recently completed his PhDon implementing smart materials and technologies for medicalemergency airway access devices. Siena’s research interests includeinvestigative research relating to the use of smart materials andtechnologies for medical applications, medical product and devicedesign, 3D printing, emerging technologies and materials and theaccurate assessment and measurement of health outcomes.– Qualification: PhD– Designation: Lecturer– Email: luke.siena@ntu.ac.uk• Marie Mc Carthy is Senior Director Product Innovation, is part of themultidisciplinary Innovation Team at ICON PLC. She has specificresponsibility for developing solutions in the direct to patient paradigmand remote patient monitoring. Her focus has been that of the use ofwearables and sensors in clinical trials. Evaluating the potential, thesedevices have to monitor the physical behaviours of the digital patient.She has presented at a number of Industry and Scientific Conferencesand authored over 40 publications on the use and implementation ofwearables in clinical trials. Marie has an MSc from University CollegeDublin.– Qualification:MSc– Designation: Senior Director Product Innovation– Email:Marie.McCarthy@iconplc.com• Philip Breedon is Professor of Smart Technologies at Nottingham TrentUniversity and leads the Medical Engineering Design Research group.His research interests and latest projects centre on new and emergingtechnologies and materials. This includes wearable technologies, 3Dprinting of pathological models, additive and subtractive manufacturingfor medical applications, surgical robotics, cardiovascular devices,extended reality, the surgical pathway and investigative research relatedto the utilisation of ‘smart materials’ for medical applications. He and amultidisciplinary research team are currently working on thedevelopment of a number of medical device applications.– Qualification: PhD– Designation: Head of Medical Engineering Design ResearchGroup.– Email: philip.breedon@ntu.ac.ukFundingThis research project was match funded PHD program by Nottingham TrentUniversity, 50 Shakespeare Street, Nottingham, United Kingdom; and ICONPLC, South County Business Park, Leopardstown, Dublin 18, IrelandAvailability of data andmaterialsThe datasets generated and/or analysed during the current study are notpublicly available due them containing information that could compromiseresearch participant privacy/consent.Ethics approval and consent to participateThe study was approved by the Joint Inter-College Ethics Committee (JICEC) atNottingham Trent University (reference JICEC1819-10). All participantsprovided written informed consent and were able and willing to participate.Consent for publicationNot applicable.Competing interestsThe authors declare that they have no known competing financial interests orpersonal relationships that could have appeared to influence the workreported in this paper.Author details1School of Science and Technology, Nottingham Trent University, Clifton Lane,NG11 8NS Nottingham, UK. 2Department of Psychology, University of BritishColumbia in Vancouver, West Mall, V6T 1Z4 Vancouver, Canada. 3School OfArchitecture Design & Built Environment, Nottingham Trent University,Goldsmith Street, NG1 4FQ Nottingham, UK. 4ICON PLC., South CountyBusiness Park, Dublin, Ireland.Received: 16 April 2020 Accepted: 9 November 2020References1. Cacabelos R. Parkinson’s disease: from pathogenesis topharmacogenomics. Int J Mol Sci. 2017;18(3):551.2. Jankovic J. Parkinson’s disease: clinical features and diagnosis. J NeurolNeurosurg Psychiatry. 2008;79(4):368–76.3. Weintraub D, Comella CL, Horn S. Parkinson’s disease–part 1:Pathophysiology, symptoms, burden, diagnosis, and assessment. Am JManag Care. 2008;14(2 Suppl):40–48.4. Parkinson’s Foundation. Statistics. Parkinson’s Foundation. 2018. http://parkinson.org/Understanding-Parkinsons/Causes-and-Statistics/Statistics.Accessed 12 Nov 2020.5. Parkinson’s UK. Facts and Figures about Parkinson’s for Journalists.Parkinson’s UK. 2018. https://www.parkinsons.org.uk/about-us/media-and-press-office. Accessed 12 Nov 2020.6. Caslake R, Taylor KS, Counsell CE. Parkinson’s disease misdiagnosed asstroke. Case Reports. 2009.7. Schapira AH, Obeso J. Timing of treatment initiation in parkinson’sdisease: a need for reappraisal? Ann Neurol. 2006;59(3):559–62.8. Seifert KD, Wiener JI. The impact of datscan on the diagnosis andmanagement of movement disorders: A retrospective study. Am JNeurodegener Dis. 2013;2(1):29.9. Martinez-Martin P, Rodriguez-Blazquez C, Forjaz MJ, Chaudhuri KR.Guide to assessment scales in Parkinson’s disease. Tarporley, UnitedKingdom: Springer; 2014.10. Falup-Pecurariu C, Ferreira J, Martinez-Martin P, Chaudhuri KR.Movement disorders curricula: Springer; 2017, pp. 1–453. https://doi.org/10.1007/978-3-7091-1628-9.11. Ramaker C, Marinus J, Stiggelbout AM, van Hilten BJ. Systematicevaluation of rating scales for impairment and disability in parkinson’sdisease. Mov Disord. 2002;17(5):867–76. https://doi.org/10.1002/mds.10248.12. Goetz CG, Poewe W, Rascol O, Sampaio C, Stebbins GT, Counsell C,Giladi N, Holloway RG, Moore CG, Wenning GK, et al. Movementdisorder society task force report on the hoehn and yahr staging scale:status and recommendations the movement disorder society task forceon rating scales for parkinson’s disease. Mov Disord. 2004;19(9):1020–8.13. Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez-MartinP, Poewe W, Sampaio C, Stern MB, Dodel R, et al. Movement disordersociety-sponsored revision of the unified parkinson’s disease rating scale(mds-updrs): scale presentation and clinimetric testing results. MovDisord Off J Mov Disord Soci. 2008;23(15):2129–70.14. Hoehn MM, Yahr MD, Others. Parkinsonism: onset, progression, andmortality. Neurology. 1998;17(5):318.15. Bhidayasiri R, Martinez-Martin P. Clinical assessments in parkinson’sdisease: Scales and monitoring. Int Rev Neurobiol. 2017;132:129–82.https://doi.org/10.1016/BS.IRN.2017.01.001.AlMahadin et al. BMC Neurology (2020) 20:419 Page 12 of 1316. Perlmutter JS. Assessment of parkinson disease manifestations. CurrProtocol Neurosci. 2009;49(1):10–1. https://doi.org/10.1002/0471142301.ns1001s49.17. Bot BM, Suver C, Neto EC, Kellen M, Klein A, Bare C, Doerr M, Pratap A,Wilbanks J, Dorsey ER, et al. The mpower study, parkinson disease mobiledata collected using researchkit. Sci data. 2016;3(1):1–9.18. Ossig C, Antonini A, Buhmann C, Classen J, Csoti I, Falkenburger B,Schwarz M, Winkler J, Storch A. Wearable sensor-based objectiveassessment of motor symptoms in parkinson’s disease. J Neural Transm.2016;123(1):57–64.19. Silva de Lima AL, Hahn T, de Vries NM, Cohen E, Bataille L, Little MA,Baldus H, Bloem BR, Faber MJ, Silva d. L., Hahn T, de Vries MN, Cohen E,Bataille L, Little MA, Baldus H, Bloem BR, Faber MJ. Large-scale wearableensor deployment in parkinson’s patients: The parkinson@home studyprotocol. JMIR Res Protocol. 2016;5(3):e172. https://doi.org/10.2196/resprot.5990.20. Palmer JL, Coats MA, Roe CM, Hanko SM, Xiong C, Morris JC. Unifiedparkinson’s disease rating scale-motor exam: Inter-rater reliability ofadvanced practice nurse and neurologist assessments. J Adv Nurs.2010;66(6):1382–7. https://doi.org/10.1111/j.1365-2648.2010.05313.x.21. Post B, Merkus MP, de Bie RMA, de Haan RJ, Speelman JD. Unifiedparkinson’s disease rating scale motor examination: Are ratings of nurses,residents in neurology, and movement disorders specialistsinterchangeable? Mov Disord. 2005;20(12):1577–84. https://doi.org/10.1002/mds.20640.22. Siderowf A, McDermott M, Kieburtz K, Blindauer K, Plumb S, Shoulson I.Test-retest reliability of the unified parkinson’s disease rating scale inpatients with early parkinson’s disease: Results from a multicenter clinicaltrial. Mov Disord. 2002;17:758–63. https://doi.org/10.1002/mds.10011.23. Fisher JM, Hammerla NY, Rochester L, Andras P, Walker RW. Body-wornsensors in parkinson’s disease: Evaluating their acceptability to patients.Telemed e-Health. 2016;22(1):63–69.24. Poewe W. Non-motor symptoms in parkinson’s disease. Eur J Neurol.2008;15:14–20.25. Richards M, Marder K, Cote L, Mayeux R. Reliability of symptom onsetassessment in parkinson’s disease. Mov Disord. 1994;9(3):340–2. https://doi.org/10.1002/mds.870090313.26. NICE. Parkinson’s disease – management. 2018. https://cks.nice.org.uk/parkinsons-disease#!management. Accessed 14 Aug 2019.27. De Lima ALS, Hahn T, Evers LJ, De Vries NM, Cohen E, Afek M, Bataille L,Daeschler M, Claes K, Boroojerdi B, et al. Feasibility of large-scaledeployment of multiple wearable sensors in parkinson’s disease. PLoSONE. 2017;12(12):e0189161.28. Chen H, Xue M, Mei Z, Bambang Oetomo S, Chen W. A review ofwearable sensor systems for monitoring body movements of neonates.Sensors. 2016;16(12):2134.29. Hubble RP, Naughton GA, Silburn PA, Cole MH. Wearable sensor use forassessing standing balance and walking stability in people withparkinson’s disease: a systematic review. PloS ONE. 2015;10(4):e0123705.30. Jalloul N. Wearable sensors for the monitoring of movement disorders.Biomed J. 2018;41(4):249–53.31. Johansson D, Malmgren K, Murphy MA. Wearable sensors for clinicalapplications in epilepsy, parkinson’s disease, and stroke: amixed-methods systematic review. J Neurol. 2018;265(8):1740–52.32. Rovini E, Maremmani C, Cavallo F. How wearable sensors can supportparkinson’s disease diagnosis and treatment: a systematic review. FrontNeurosci. 2017;11:555.33. Hasan H, Athauda DS, Foltynie T, Noyce AJ. Technologies assessing limbbradykinesia in parkinson’s disease. J Parkinson’s Dis. 2017;7(1):65–77.34. Espay AJ, Hausdorff JM, Sánchez-Ferro Á, Klucken J, Merola A, Bonato P,Paul SS, Horak FB, Vizcarra JA, Mestre TA, et al. A roadmap forimplementation of patient-centered digital outcome measures inparkinson’s disease obtained using mobile health technologies. MovDisord. 2019;34(5):657–63.35. Godinho C, Domingos J, Cunha G, Santos AT, Fernandes RM, Abreu D,Gonçalves N, Matthews H, Isaacs T, Duffen J, Al-Jawad A, Larsen F,Serrano A, Weber P, Thoms A, Sollinger S, Graessner H, Maetzler W,Ferreira JJ. A systematic review of the characteristics and validity ofmonitoring technologies to assess parkinson’s disease. JNeuroEngineering Rehabil. 2016;13(1):24. https://doi.org/10.1186/s12984-016-0136-7.36. Odin P, Chaudhuri KR, Volkmann J, Antonini A, Storch A, Dietrichs E,Pirtošek Z, Henriksen T, Horne M, Devos D, Bergquist F. Viewpoint andpractical recommendations from a movement disorder specialist panelon objective measurement in the clinical management of parkinson’sdisease. NPJ Parkinson’s Dis. 2018;4(1):14. https://doi.org/10.1038/s41531-018-0051-7.37. Money AG, Barnett J, Kuljis J, Craven MP, Martin JL, Young T. The role ofthe user within the medical device design and development process:medical device manufacturers’ perspectives. BMC Med Inform DecisMaking. 2011;11(1):15.38. Shah SGS, Robinson I, AlShawi S. Developing medical devicetechnologies from users’ perspectives: a theoretical framework forinvolving users in the development process. Int J Technol Assess HealthCare. 2009;25(4):514–21.39. Bergmann JH, Chandaria V, McGregor A. Wearable and implantablesensors: the patient’s perspective. Sensors. 2012;12(12):16695–709.40. Sawyer D, Aziz K, Backinger C, Beers E, Lowery A, Sykes S. Anintroduction to human factors in medical devices. Department of Healthand Human Services, US, Public Health Service, Food and DrugAdministration, Center for Devices and Radiological Health. 1996.41. Alwan M, Wiley D, Nobel J. State of technology in aging services. Centerfor Aging Services Technology (CAST). 2007.42. New England Healthcare Institute. Remote Physiological Monitoring.NEHI. 2008. https://www.nehi.net/writable/publication_files/file/rpm_research_update_onepager_2009.pdf.43. Hare J, Thomas G, Andrews C, Eggbeer D, et al. Generative participatorydesign for interactive medical devices. In: DS 84: Proceedings of theDESIGN 2016 14th International Design Conference. Dubrovnik: TheDesign Society’s; 2016. p. 1865–74.44. Steen M, Kuijt-Evers L, Klok J. Early user involvement in research anddesign projects–a review of methods and practices. In: 23rd EGOSColloquium, vol. 5. Vienna: European Group for Organizational Studies(EGOS); 2007. p. 1–21.45. Bruno E, Simblett S, Lang A, Biondi A, Odoi C, Schulze-Bonhage A,Wykes T, Richardson MP, Consortium R-C, et al. Wearable technology inepilepsy: The views of patients, caregivers, and healthcare professionals.Epilepsy Behav. 2018;85:141–9.46. Ferreira JJ, Godinho C, Santos AT, Domingos J, Abreu D, Lobo R,Gonçalves N, Barra M, Larsen F, Fagerbakke Ø, et al. Quantitativehome-based assessment of parkinson’s symptoms: The sense-parkfeasibility and usability study. BMC Neurol. 2015;15(1):89.47. Hoppe C, Feldmann M, Blachut B, Surges R, Elger CE, Helmstaedter C.Novel techniques for automated seizure registration: patients’ wants andneeds. Epilepsy Behav. 2015;52:1–7.48. Mercer K, Giangregorio L, Schneider E, Chilana P, Li M, Grindrod K.Acceptance of commercially available wearable activity trackers amongadults aged over 50 and with chronic illness: a mixed-methodsevaluation. JMIR mHealth uHealth. 2016;4(1):7.49. Ozanne A, Johansson D, Hällgren Graneheim U, Malmgren K, BergquistF, Alt Murphy M. Wearables in epilepsy and parkinson’s disease-a focusgroup study. Acta Neurologica Scandinavica. 2018;137(2):188–94.50. Papi E, Belsi A, McGregor AH. A knee monitoring device and thepreferences of patients living with osteoarthritis: a qualitative study. BMJOpen. 2015;5(9).51. Peng G, Garcia LMS, Nunes M, Zhang N. Identifying user requirements ofwearable healthcare technologies for chinese ageing population. In: 2016IEEE International Smart Cities Conference (ISC2). Trento: IEEE; 2016. p.1–6.52. Santiago A, Langston JW, Gandhy R, Dhall R, Brillman S, Rees L, BarlowC. Qualitative evaluation of the personal kinetigraph tm movementrecording system in a parkinson’s clinic. J Parkinson’s Dis. 2019;9(1):207–19.53. Simone LK, Sundarrajan N, Luo X, Jia Y, Kamper DG. A low costinstrumented glove for extended monitoring and functional handassessment. J Neurosci Methods. 2007;160(2):335–48.54. Thilo FJ, Hahn S, Halfens RJ, Schols JM. Usability of a wearable falldetection prototype from the perspective of older people–a real fieldtesting approach. J Clin Nurs. 2019;28(1-2):310–20.55. Xing F, Peng G, Liang T, Jiang J. Challenges for deploying iot wearablemedical devices among the ageing population. In: InternationalConference on Distributed, Ambient, and Pervasive Interactions. Cham:Springer; 2018. p. 286–95.AlMahadin et al. BMC Neurology (2020) 20:419 Page 13 of 1356. Zhao Y, Heida T, van Wegen EE, Bloem BR, van Wezel RJ. E-healthsupport in people with parkinson’s disease with smart glasses: a survey ofuser requirements and expectations in the netherlands. J Parkinson’s Dis.2015;5(2):369–78.57. Beiske B. Research methods. Uses and limitations of questionnaires,interviews, and case studies. BoD–Books on Demand. Munich:GRINVerlag; 2007.58. Mathers N, Fox N, Hunn A. Surveys and questionnaires. The NIHRresearch design service for the East Midlands/Yorkshire & the Humber.2007. https://www.rds-yh.nihr.ac.uk/wp-content/uploads/2013/05/12_Surveys_and_Questionnaires_Revision_2009.pdf.59. Braun V, Clarke V. Successful qualitative research: a practical guide forbeginners. London: sage; 2013.60. Lambert SD, Loiselle CG. Combining individual interviews and focusgroups to enhance data richness. J Adv Nurs. 2008;62(2):228–37.61. Jellinger KA, Logroscino G, Rizzo G, Copetti M, Arcuti S, Martino D,Fontana A. Accuracy of clinical diagnosis of parkinson disease: Asystematic review and meta-analysisauthor response. Neurology.2016;87(2):237–8.62. Small SA. Age-related memory decline: current concepts and futuredirections. Arch Neurol. 2001;58(3):360–4.63. Amanzio M, Monteverdi S, Giordano A, Soliveri P, Filippi P, Geminiani G.Impaired awareness of movement disorders in parkinson’s disease. BrainCogn. 2010;72(3):337–46.64. de Lima ALS, Hahn T, de Vries NM, Cohen E, Bataille L, Little MA, BaldusH, Bloem BR, Faber MJ. Large-scale wearable sensor deployment inparkinson’s patients: the parkinson@ home study protocol. JMIR ResProtocol. 2016;5(3):172.65. Vassli LT, Farshchian BA. Acceptance of health-related ICT among elderlypeople living in the community: A systematic review of qualitativeevidence. Int J Hum Comput Interact. 2018;34(2):99–116.66. Gövercin M, Költzsch Y, Meis M, Wegel S, Gietzelt M, Spehr J,Winkelbach S, Marschollek M, Steinhagen-Thiessen E. Defining the userrequirements for wearable and optical fall prediction and fall detectiondevices for home use. Inform Health Soc Care. 2010;35(3-4):177–87.67. Profita HP, Clawson J, Gilliland S, Zeagler C, Starner T, Budd J, Do EY-L.Don’t mind me touching my wrist: a case study of interacting withon-body technology in public. In: Proceedings of the 2013 InternationalSymposium on Wearable Computers; 2013. p. 89–96.68. United Nations. Ageing. 2019. p. 5–6. https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/files/documents/2020/Jan/un_2019_worldpopulationageing_report.pdf. Accessed 12 Nov2020.69. Charlton GS, Barrow CJ. Coping and self-help group membership inparkinson’s disease: an exploratory qualitative study. Health Soc CareCommunity. 2002;10(6):472–8.70. Caap-Ahlgren M, PhD LL, Ove Dehlin M. Older swedish women’sexperiences of living with symptoms related to parkinson’s disease. J AdvNurs. 2002;39(1):87–95.71. Nijhof G. Parkinson’s disease as a problem of shame in public appearance.Sociol Health Illn. 1995;17(2):193–205.72. Thordardottir B, Nilsson MH, Iwarsson S, Haak M. “you plan, but younever know”–participation among people with different levels of severityof parkinson’s disease. Disabil Rehabil. 2014;36(26):2216–24.73. Mancini M, El-Gohary M, Pearson S, McNames J, Schlueter H, Nutt JG,King LA, Horak FB. Continuous monitoring of turning in parkinson’sdisease: rehabilitation potential. NeuroRehabilitation. 2015;37(1):3–10.74. Downey C, Brown J, Jayne D, Randell R. Patient attitudes towardsremote continuous vital signs monitoring on general surgery wards: aninterview study. Int J Med Inform. 2018;114:52–56.75. Allen NE, Schwarzel AK, Canning CG. Recurrent falls in parkinson’sdisease: a systematic review. Parkinson’s Dis. 2013;2013.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.
Article
eng
Reviewed
Vancouver : University of British Columbia Library
BioMed Central
Attribution 4.0 International (CC BY 4.0)
Faculty
Parkinson’s disease
Focus groups
Interviews
Healthcare professionals
Patients
Wearable devices
Qualitative analysis
Preferences
Parkinson’s disease: current assessment methods and wearable devices for evaluation of movement disorder motor symptoms - a patient and healthcare professional perspective
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