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Wu R, Calligan M, Son T, Rakhra H, de Lara E, Mariakakis A, Gershon AS. Impressions and Perceptions of a Smartphone and Smartwatch Self-Management Tool for Patients With COPD: A Qualitative Study. COPD 2024; 21:2277158. [PMID: 38348964 DOI: 10.1080/15412555.2023.2277158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 10/25/2023] [Indexed: 02/15/2024]
Abstract
BACKGROUND Patients with chronic obstructive pulmonary disease (COPD) often do not seek care until they experience an exacerbation. Improving self-management for these patients may increase health-related quality of life and reduce hospitalizations. Patients are willing to use wearable technology for real-time data reporting and perceive mobile technology as potentially helpful in COPD management, but there are many barriers to the uptake of these technologies. OBJECTIVE We aimed to understand patients' experiences using a wearable and mobile app and identify areas for improvement. METHODS We conducted semi-structured interviews as part of a larger prospective cohort study wherein patients used a wearable and app for 6 months. We asked which features patients found accessible, acceptable and useful. RESULTS We completed 26 interviews. We summarized our research findings into four main themes: (1) information, support and reassurance, (2) barriers to adoption, (3) impact on communication with health care providers, and (4) opportunities for improvement. Most patients found the feedback received through the app to be reassuring and useful. Some patients experienced technical difficulties with the app and found the wearable to be uncomfortable. CONCLUSIONS Patients found a wearable device and mobile application to be acceptable and useful for the management of COPD. We identified barriers to adoption and opportunities for improvement to the design of our app. Further research is needed to understand what people with COPD and their healthcare providers want and will use in a mobile app and wearable for COPD management.
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Affiliation(s)
- Robert Wu
- Division of General Internal Medicine, University Health Network, Toronto, Canada
- Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Maryann Calligan
- Division of General Internal Medicine, University Health Network, Toronto, Canada
| | - Tanya Son
- Division of General Internal Medicine, University Health Network, Toronto, Canada
| | - Harshmeet Rakhra
- Division of General Internal Medicine, University Health Network, Toronto, Canada
| | - Eyal de Lara
- Department of Computer Science, University of Toronto, Toronto, Canada
| | - Alex Mariakakis
- Department of Computer Science, University of Toronto, Toronto, Canada
| | - Andrea S Gershon
- Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Canada
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
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Liao L, Li X, Chong T, Chen Q, Xu Z, Huang B, Chen M, Li H, Wei Z, Shao Y, Lu J, Pang R, Li X, Wang Y. Efficacy and safety of tibial nerve stimulation using a wearable device for overactive bladder. BJU Int 2024; 133:760-769. [PMID: 38468422 DOI: 10.1111/bju.16330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
OBJECTIVE To evaluate the efficacy and safety of a wearable, smartphone-controlled, rechargeable transcutaneous tibial nerve stimulation (TTNS) device in patients with overactive bladder (OAB). PATIENTS AND METHODS This multicentre, prospective, single-blind, randomised clinical trial included eligible patients with OAB symptoms who were randomly assigned to the stimulation group or sham group. The primary efficacy outcome was change from baseline in voiding frequency/24 h after 4 weeks of treatment. The secondary efficacy outcomes included changes in bladder diary outcomes (urgency score/void, nocturia episodes/day, micturition volume/void, and incontinence episodes/day), questionnaires on Overactive Bladder Symptom Score (OABSS), Patient Perception of Bladder Condition (PPBC), and American Urological Association Symptom Index Quality of Life Score (AUA-SI-QoL) at baseline and after 4 weeks of treatment. Device-related adverse events (AEs) were also evaluated. RESULTS In the full analysis set (FAS), the mean (sd) change of voiding frequency/24 h in the stimulation group and sham group at 4 weeks were -3.5 (2.9) and -0.6 (2.4), respectively (P < 0.01). Similar results were obtained in the per-protocol set (PPS): -3.5 (2.9) vs -0.4 (2.3) (P < 0.01). In the FAS and PPS, micturition volume/void significantly improved at 4 weeks (P = 0.01 and P = 0.02). PPBC improvement almost reached significance in the FAS (P = 0.05), while it was significant in the PPS (P = 0.02). In the FAS and PPS, AUA-SI-QoL significantly improved at 4 weeks in the two groups (P < 0.01 and P < 0.01), whereas there were no significant differences in urgency score/void, nocturia episodes/day or OABSS between the groups. Also, no device-related serious AEs were reported. CONCLUSIONS The non-invasive neuromodulation technique using the novel ambulatory TTNS device is effective and safe for treating OAB. Its convenience and easy maintenance make it a new potential home-based treatment modality. Future studies are warranted to confirm its longer-term efficacy.
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Affiliation(s)
- Limin Liao
- Department of Urology, China Rehabilitation Research Centre, China Rehabilitation Science Institute, Rehabilitation School of Capital Medical University, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Xing Li
- Department of Urology, China Rehabilitation Research Centre, China Rehabilitation Science Institute, Rehabilitation School of Capital Medical University, Beijing, China
| | - Tie Chong
- Department of Urology, Second Affifiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qi Chen
- Department of Urology, Second Affifiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zhihui Xu
- Department of Urology, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Banggao Huang
- Department of Urology, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Min Chen
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Haoran Li
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhongqing Wei
- Department of Urology, Second Affifiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yunpeng Shao
- Department of Urology, Second Affifiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jianxin Lu
- Department of Urology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ran Pang
- Department of Urology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xunhua Li
- Department of Urology, China Rehabilitation Research Centre, China Rehabilitation Science Institute, Rehabilitation School of Capital Medical University, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Yiming Wang
- Department of Urology, China Rehabilitation Research Centre, China Rehabilitation Science Institute, Rehabilitation School of Capital Medical University, Beijing, China
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Danielsson ML, Vergeer M, Plasqui G, Baumgart JK. Accuracy of the Apple Watch Series 4 and Fitbit Versa for Assessing Energy Expenditure and Heart Rate of Wheelchair Users During Treadmill Wheelchair Propulsion: Cross-sectional Study. JMIR Form Res 2024; 8:e52312. [PMID: 38713497 DOI: 10.2196/52312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 02/19/2024] [Accepted: 02/26/2024] [Indexed: 05/08/2024] Open
Abstract
BACKGROUND The Apple Watch (AW) Series 1 provides energy expenditure (EE) for wheelchair users but was found to be inaccurate with an error of approximately 30%, and the corresponding error for heart rate (HR) provided by the Fitbit Charge 2 was approximately 10% to 20%. Improved accuracy of estimated EE and HR is expected with newer editions of these smart watches (SWs). OBJECTIVE This study aims to assess the accuracy of the AW Series 4 (wheelchair-specific setting) and the Fitbit Versa (treadmill running mode) for estimating EE and HR during wheelchair propulsion at different intensities. METHODS Data from 20 manual wheelchair users (male: n=11, female: n=9; body mass: mean 75, SD 19 kg) and 20 people without a disability (male: n=11, female: n=9; body mass: mean 75, SD 11 kg) were included. Three 4-minute wheelchair propulsion stages at increasing speed were performed on 3 separate test days (0.5%, 2.5%, or 5% incline), while EE and HR were collected by criterion devices and the AW or Fitbit. The mean absolute percentage error (MAPE) was used to indicate the absolute agreement between the criterion device and SWs for EE and HR. Additionally, linear mixed model analyses assessed the effect of exercise intensity, sex, and group on the SW error. Interclass correlation coefficients were used to assess relative agreement between criterion devices and SWs. RESULTS The AW underestimated EE with MAPEs of 29.2% (SD 22%) in wheelchair users and 30% (SD 12%) in people without a disability. The Fitbit overestimated EE with MAPEs of 73.9% (SD 7%) in wheelchair users and 44.7% (SD 38%) in people without a disability. Both SWs underestimated HR. The device error for EE and HR increased with intensity for both SWs (all comparisons: P<.001), and the only significant difference between groups was found for HR in the AW (-5.27 beats/min for wheelchair users; P=.02). There was a significant effect of sex on the estimation error in EE, with worse accuracy for the AW (-0.69 kcal/min; P<.001) and better accuracy for the Fitbit (-2.08 kcal/min; P<.001) in female participants. For HR, sex differences were found only for the AW, with a smaller error in female participants (5.23 beats/min; P=.02). Interclass correlation coefficients showed poor to moderate relative agreement for both SWs apart from 2 stage-incline combinations (AW: 0.12-0.57 for EE and 0.11-0.86 for HR; Fitbit: 0.06-0.85 for EE and 0.03-0.29 for HR). CONCLUSIONS Neither the AW nor Fitbit were sufficiently accurate for estimating EE or HR during wheelchair propulsion. The AW underestimated EE and the Fitbit overestimated EE, and both SWs underestimated HR. Caution is hence required when using SWs as a tool for training intensity regulation and energy balance or imbalance in wheelchair users.
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Affiliation(s)
- Marius Lyng Danielsson
- Centre for Elite Sports Research, Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Melanie Vergeer
- Centre for Elite Sports Research, Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Nutrition and Movement Sciences, Maastricht University, Maastricht, Netherlands
| | - Guy Plasqui
- Department of Nutrition and Movement Sciences, Maastricht University, Maastricht, Netherlands
| | - Julia Kathrin Baumgart
- Centre for Elite Sports Research, Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
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de Graaf D, de Vries NM, van de Zande T, Schimmel JJP, Shin S, Kowahl N, Barman P, Kapur R, Marks WJ, van 't Hul A, Bloem B. Measuring Physical Functioning Using Wearable Sensors in Parkinson Disease and Chronic Obstructive Pulmonary Disease (the Accuracy of Digital Assessment of Performance Trial Study): Protocol for a Prospective Observational Study. JMIR Res Protoc 2024; 13:e55452. [PMID: 38713508 DOI: 10.2196/55452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/07/2024] [Accepted: 03/11/2024] [Indexed: 05/08/2024] Open
Abstract
BACKGROUND Physical capacity and physical activity are important aspects of physical functioning and quality of life in people with a chronic disease such as Parkinson disease (PD) or chronic obstructive pulmonary disease (COPD). Both physical capacity and physical activity are currently measured in the clinic using standardized questionnaires and tests, such as the 6-minute walk test (6MWT) and the Timed Up and Go test (TUG). However, relying only on in-clinic tests is suboptimal since they offer limited information on how a person functions in daily life and how functioning fluctuates throughout the day. Wearable sensor technology may offer a solution that enables us to better understand true physical functioning in daily life. OBJECTIVE We aim to study whether device-assisted versions of 6MWT and TUG, such that the tests can be performed independently at home using a smartwatch, is a valid and reliable way to measure the performance compared to a supervised, in-clinic test. METHODS This is a decentralized, prospective, observational study including 100 people with PD and 100 with COPD. The inclusion criteria are broad: age ≥18 years, able to walk independently, and no co-occurrence of PD and COPD. Participants are followed for 15 weeks with 4 in-clinic visits, once every 5 weeks. Outcomes include several walking tests, cognitive tests, and disease-specific questionnaires accompanied by data collection using wearable devices (the Verily Study Watch and Modus StepWatch). Additionally, during the last 10 weeks of this study, participants will follow an aerobic exercise training program aiming to increase physical capacity, creating the opportunity to study the responsiveness of the remote 6MWT. RESULTS In total, 89 people with PD and 65 people with COPD were included in this study. Data analysis will start in April 2024. CONCLUSIONS The results of this study will provide information on the measurement properties of the device-assisted 6MWT and TUG in the clinic and at home. When reliable and valid, this can contribute to a better understanding of a person's physical capacity in real life, which makes it possible to personalize treatment options. TRIAL REGISTRATION ClinicalTrials.gov NCT05756075; https://clinicaltrials.gov/study/NCT05756075. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/55452.
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Affiliation(s)
- Debbie de Graaf
- Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, Netherlands
| | - Nienke M de Vries
- Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, Netherlands
| | - Tessa van de Zande
- Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, Netherlands
| | - Janneke J P Schimmel
- Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, Netherlands
| | - Sooyoon Shin
- Verily Life Sciences, South San Fransisco, CA, United States
| | - Nathan Kowahl
- Verily Life Sciences, South San Fransisco, CA, United States
| | - Poulami Barman
- Verily Life Sciences, South San Fransisco, CA, United States
| | - Ritu Kapur
- Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, Netherlands
- Verily Life Sciences, South San Fransisco, CA, United States
| | - William J Marks
- Verily Life Sciences, South San Fransisco, CA, United States
| | - Alex van 't Hul
- Radboud University Medical Center, Radboud Institute for Health Sciences, Department of Respiratory Diseases, Nijmegen, Netherlands
| | - Bastiaan Bloem
- Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, Netherlands
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Iqbal FM, Aggarwal R, Joshi M, King D, Martin G, Khan S, Wright M, Ashrafian H, Darzi A. Barriers to and Facilitators of Key Stakeholders Influencing Successful Digital Implementation of Remote Monitoring Solutions: Mixed Methods Analysis. JMIR Hum Factors 2024; 11:e49769. [PMID: 37338929 DOI: 10.2196/49769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 01/26/2024] [Accepted: 04/07/2024] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND Implementation of remote monitoring solutions and digital alerting tools in health care has historically been challenging, despite the impetus provided by the COVID-19 pandemic. To date, a health systems-based approach to systematically describe barriers and facilitators across multiple domains has not been undertaken. OBJECTIVE We aimed to undertake a comprehensive mixed methods analysis of barriers and facilitators for successful implementation of remote monitoring and digital alerting tools in complex health organizations. METHODS A mixed methods approach using a modified Technology Acceptance Model questionnaire and semistructured interviews mapped to the validated fit among humans, organizations, and technology (HOT-fit) framework was undertaken. Likert frequency responses and deductive thematic analyses were performed. RESULTS A total of 11 participants responded to the questionnaire and 18 participants to the interviews. Key barriers and facilitators could be mapped onto 6 dimensions, which incorporated aspects of digitization: system use (human), user satisfaction (human), environment (organization), structure (organization), information and service quality (technology), and system quality (technology). CONCLUSIONS The recommendations proposed can enhance the potential for future remote sensing solutions to be more successfully integrated in health care practice, resulting in more successful use of "virtual wards." TRIAL REGISTRATION ClinicalTrials.gov NCT05321004; https://www.clinicaltrials.gov/study/NCT05321004.
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Affiliation(s)
| | - Ravi Aggarwal
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Meera Joshi
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Dominic King
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Guy Martin
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Sadia Khan
- West Middlesex University Hospital, London, United Kingdom
| | - Mike Wright
- Innovation Business Partner, Chelsea and Westminster NHS Trust, London, United Kingdom
| | - Hutan Ashrafian
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Ara Darzi
- Division of Surgery, Imperial College London, London, United Kingdom
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Martin J, Rueda A, Lee GH, Tassone VK, Park H, Ivanov M, Darnell BC, Beavers L, Campbell DM, Nguyen B, Torres A, Jung H, Lou W, Nazarov A, Ashbaugh A, Kapralos B, Litz B, Jetly R, Dubrowski A, Strudwick G, Krishnan S, Bhat V. Digital Interventions to Understand and Mitigate Stress Response: Protocol for Process and Content Evaluation of a Cohort Study. JMIR Res Protoc 2024; 13:e54180. [PMID: 38709554 DOI: 10.2196/54180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/04/2024] [Accepted: 03/06/2024] [Indexed: 05/07/2024] Open
Abstract
BACKGROUND Staffing and resource shortages, especially during the COVID-19 pandemic, have increased stress levels among health care workers. Many health care workers have reported feeling unable to maintain the quality of care expected within their profession, which, at times, may lead to moral distress and moral injury. Currently, interventions for moral distress and moral injury are limited. OBJECTIVE This study has the following aims: (1) to characterize and reduce stress and moral distress related to decision-making in morally complex situations using a virtual reality (VR) scenario and a didactic intervention; (2) to identify features contributing to mental health outcomes using wearable, physiological, and self-reported questionnaire data; and (3) to create a personal digital phenotype profile that characterizes stress and moral distress at the individual level. METHODS This will be a single cohort, pre- and posttest study of 100 nursing professionals in Ontario, Canada. Participants will undergo a VR simulation that requires them to make morally complex decisions related to patient care, which will be administered before and after an educational video on techniques to mitigate distress. During the VR session, participants will complete questionnaires measuring their distress and moral distress, and physiological data (electrocardiogram, electrodermal activity, plethysmography, and respiration) will be collected to assess their stress response. In a subsequent 12-week follow-up period, participants will complete regular assessments measuring clinical outcomes, including distress, moral distress, anxiety, depression, and loneliness. A wearable device will also be used to collect continuous data for 2 weeks before, throughout, and for 12 weeks after the VR session. A pre-post comparison will be conducted to analyze the effects of the VR intervention, and machine learning will be used to create a personal digital phenotype profile for each participant using the physiological, wearable, and self-reported data. Finally, thematic analysis of post-VR debriefing sessions and exit interviews will examine reoccurring codes and overarching themes expressed across participants' experiences. RESULTS The study was funded in 2022 and received research ethics board approval in April 2023. The study is ongoing. CONCLUSIONS It is expected that the VR scenario will elicit stress and moral distress. Additionally, the didactic intervention is anticipated to improve understanding of and decrease feelings of stress and moral distress. Models of digital phenotypes developed and integrated with wearables could allow for the prediction of risk and the assessment of treatment responses in individuals experiencing moral distress in real-time and naturalistic contexts. This paradigm could also be used in other populations prone to moral distress and injury, such as military and public safety personnel. TRIAL REGISTRATION ClinicalTrials.gov NCT05923398; https://clinicaltrials.gov/study/NCT05923398. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/54180.
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Affiliation(s)
- Josh Martin
- Interventional Psychiatry Program, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Alice Rueda
- Interventional Psychiatry Program, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Gyu Hee Lee
- Interventional Psychiatry Program, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Vanessa K Tassone
- Interventional Psychiatry Program, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Haley Park
- Interventional Psychiatry Program, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Martin Ivanov
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada
| | - Benjamin C Darnell
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
| | - Lindsay Beavers
- Allan Waters Family Simulation Program, Unity Health Toronto, Toronto, ON, Canada
- Department of Physical Therapy, University of Toronto, Toronto, ON, Canada
| | - Douglas M Campbell
- Allan Waters Family Simulation Program, Unity Health Toronto, Toronto, ON, Canada
- Neonatal Intensive Care Unit, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
- Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Binh Nguyen
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada
| | - Andrei Torres
- maxSIMhealth Group, Ontario Tech University, Oshawa, ON, Canada
| | - Hyejung Jung
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Anthony Nazarov
- MacDonald Franklin OSI Research Centre, Lawson Health Research Institute, London, ON, Canada
| | - Andrea Ashbaugh
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
| | - Bill Kapralos
- maxSIMhealth Group, Ontario Tech University, Oshawa, ON, Canada
| | - Brett Litz
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
| | - Rakesh Jetly
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Adam Dubrowski
- maxSIMhealth Group, Ontario Tech University, Oshawa, ON, Canada
| | - Gillian Strudwick
- Centre For Addiction & Mental Health, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Arthur Labatt Family School of Nursing, Western University, London, ON, Canada
| | - Sridhar Krishnan
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada
| | - Venkat Bhat
- Interventional Psychiatry Program, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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7
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Lee H, Johnson Z, Denton S, Liu N, Akinwande D, Porter E, Kireev D. A non-invasive approach to skin cancer diagnosis via graphene electrical tattoos and electrical impedance tomography. Physiol Meas 2024; 45:055003. [PMID: 38599226 DOI: 10.1088/1361-6579/ad3d26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 04/10/2024] [Indexed: 04/12/2024]
Abstract
Objective.Making up one of the largest shares of diagnosed cancers worldwide, skin cancer is also one of the most treatable. However, this is contingent upon early diagnosis and correct skin cancer-type differentiation. Currently, methods for early detection that are accurate, rapid, and non-invasive are limited. However, literature demonstrating the impedance differences between benign and malignant skin cancers, as well as between different types of skin cancer, show that methods based on impedance differentiation may be promising.Approach.In this work, we propose a novel approach to rapid and non-invasive skin cancer diagnosis that leverages the technologies of difference-based electrical impedance tomography (EIT) and graphene electronic tattoos (GETs).Main results.We demonstrate the feasibility of this first-of-its-kind system using both computational numerical and experimental skin phantom models. We considered variations in skin cancer lesion impedance, size, shape, and position relative to the electrodes and evaluated the impact of using individual and multi-electrode GET (mGET) arrays. The results demonstrate that this approach has the potential to differentiate based on lesion impedance, size, and position, but additional techniques are needed to determine shape.Significance.In this way, the system proposed in this work, which combines both EIT and GET technology, exhibits potential as an entirely non-invasive and rapid approach to skin cancer diagnosis.
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Affiliation(s)
- Hannah Lee
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States of America
| | - Zane Johnson
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX, United States of America
| | - Spencer Denton
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States of America
| | - Ning Liu
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States of America
| | - Deji Akinwande
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States of America
- Microelectronics Research Center, The University of Texas at Austin, Austin, TX, United States of America
| | - Emily Porter
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States of America
- Department of Biomedical Engineering, McGill University, Montreal, Canada
| | - Dmitry Kireev
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States of America
- Microelectronics Research Center, The University of Texas at Austin, Austin, TX, United States of America
- Department of Biomedical Engineering, The University of Massachusetts Amherst, Amherst, MA, United States of America
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8
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Stieger S, Volsa S, Willinger D, Lewetz D, Batinic B. Laughter in everyday life: an event-based experience sampling method study using wrist-worn wearables. Front Psychol 2024; 15:1296955. [PMID: 38756489 PMCID: PMC11096579 DOI: 10.3389/fpsyg.2024.1296955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 04/15/2024] [Indexed: 05/18/2024] Open
Abstract
Laughter is a universal, nonverbal vocal expression of broad significance for humans. Interestingly, rather little is known about how often we laugh and how laughter is associated with our personality. In a large, event-based, experience sampling method study (N = 52; k = 9,261 assessments) using wrist-worn wearables and a physical analogue scale, we analyzed belly laughs and fit of laughter events in participants' everyday life for 4 weeks. Additionally, we assessed associations with laughter frequency such as personality, happiness, life satisfaction, gelotophobia (i.e., fear of being laughed at), and cheerfulness. Validating our new measurement approach (i.e., wearables, physical analogue scale), laughter events elicited higher happiness ratings compared to reference assessments, as expected. On average, participants reported 2.5 belly laughs per day and on every fourth day a fit of laughter. As expected, participants who were happier and more satisfied with their life laughed more frequently than unhappier, unsatisfied participants. Women and younger participants laughed significantly more than men and older participants. Regarding personality, laughter frequency was positively associated with openness and conscientiousness. No significant association was found for gelotophobia, and results for cheerfulness and related concepts were mixed. By using state-of-the-art statistical methods (i.e., recurrent event regression) for the event-based, multi-level data on laughter, we could replicate past results on laughing.
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Affiliation(s)
- Stefan Stieger
- Department of Psychology and Psychodynamics, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria
| | - Selina Volsa
- Department of Psychology and Psychodynamics, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria
| | - David Willinger
- Department of Psychology and Psychodynamics, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria
| | - David Lewetz
- Department of Psychology and Psychodynamics, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria
| | - Bernad Batinic
- Department of Work, Organizational, and Media Psychology, Johannes Kepler University, Linz, Austria
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9
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Li P, Gao C, Yu L, Gao L, Cai R, Bennett DA, Schneider JA, Buchman AS, Hu K. Delineating cognitive resilience using fractal regulation: Cross-sectional and longitudinal evidence from the Rush Memory and Aging Project. Alzheimers Dement 2024; 20:3203-3210. [PMID: 38497429 PMCID: PMC11095481 DOI: 10.1002/alz.13747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 03/19/2024]
Abstract
INTRODUCTION Degradation of fractal patterns in actigraphy independently predicts dementia risk. Such observations motivated the study to understand the role of fractal regulation in the context of neuropathologies. METHODS We examined associations of fractal regulation with neuropathologies and longitudinal cognitive changes in 533 older participants who were followed annually with actigraphy and cognitive assessments until death with brain autopsy performed. Two measures for fractal patterns were extracted from actigraphy, namely, α1 (representing the fractal regulation at time scales of <90 min) and α2 (for time scales 2 to 10 h). RESULTS We found that larger α1 was associated with lower burdens of Lewy body disease or cerebrovascular disease pathologies; both α1 and α2 were associated with cognitive decline. They explained an additional significant portion of the variance in the rate of cognitive decline above and beyond neuropathologies. DISCUSSION Fractal patterns may be used as a biomarker for cognitive resilience against dementia-related neuropathologies.
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Affiliation(s)
- Peng Li
- Department of AnesthesiaCritical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Medical Biodynamics Program, Division of Sleep and Circadian DisordersBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Division of Sleep MedicineHarvard Medical SchoolBostonMassachusettsUSA
- Broad Institute of MIT and HarvardCambridgeMassachusettsUSA
| | - Chenlu Gao
- Department of AnesthesiaCritical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Medical Biodynamics Program, Division of Sleep and Circadian DisordersBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Division of Sleep MedicineHarvard Medical SchoolBostonMassachusettsUSA
- Broad Institute of MIT and HarvardCambridgeMassachusettsUSA
| | - Lei Yu
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Lei Gao
- Department of AnesthesiaCritical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Medical Biodynamics Program, Division of Sleep and Circadian DisordersBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Division of Sleep MedicineHarvard Medical SchoolBostonMassachusettsUSA
- Broad Institute of MIT and HarvardCambridgeMassachusettsUSA
| | - Ruixue Cai
- Department of AnesthesiaCritical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Medical Biodynamics Program, Division of Sleep and Circadian DisordersBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - David A. Bennett
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Julie A. Schneider
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Aron S. Buchman
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Kun Hu
- Department of AnesthesiaCritical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Medical Biodynamics Program, Division of Sleep and Circadian DisordersBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Division of Sleep MedicineHarvard Medical SchoolBostonMassachusettsUSA
- Broad Institute of MIT and HarvardCambridgeMassachusettsUSA
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10
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Ye C, Zhao L, Yang S, Li X. Recent Research on Preparation and Application of Smart Joule Heating Fabrics. Small 2024; 20:e2309027. [PMID: 38072784 DOI: 10.1002/smll.202309027] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 11/10/2023] [Indexed: 05/03/2024]
Abstract
Multifunctional wearable heaters have attracted much attention for their effective applications in personal thermal management and medical therapy. Compared to passive heating, Joule heating offers significant advantages in terms of reusability, reliable temperature control, and versatile coupling. Joule-heated fabrics make wearable electronics smarter. This review critically discusses recent advances in Joule-heated smart fabrics, focusing on various fabrication strategies based on material-structure synergy. Specifically, various applicable conductive materials with Joule heating effect are first summarized. Subsequently, different preparation methods for Joule heating fabrics are compared, and then their various applications in smart clothing, healthcare, and visual indication are discussed. Finally, the challenges faced in developing these smart Joule heating fabrics and their possible solutions are discussed.
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Affiliation(s)
- Chunfa Ye
- School of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Longqi Zhao
- School of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Sihui Yang
- School of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Xiaoyan Li
- School of Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai, 200093, China
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11
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Vidal Bustamante CM, Coombs Iii G, Rahimi-Eichi H, Mair P, Onnela JP, Baker JT, Buckner RL. Precision Assessment of Real-World Associations Between Stress and Sleep Duration Using Actigraphy Data Collected Continuously for an Academic Year: Individual-Level Modeling Study. JMIR Form Res 2024; 8:e53441. [PMID: 38687600 PMCID: PMC11094608 DOI: 10.2196/53441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/10/2024] [Accepted: 03/07/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND Heightened stress and insufficient sleep are common in the transition to college, often co-occur, and have both been linked to negative health outcomes. A challenge concerns disentangling whether perceived stress precedes or succeeds changes in sleep. These day-to-day associations may vary across individuals, but short study periods and group-level analyses in prior research may have obscured person-specific phenotypes. OBJECTIVE This study aims to obtain stable estimates of lead-lag associations between perceived stress and objective sleep duration in the individual, unbiased by the group, by developing an individual-level linear model that can leverage intensive longitudinal data while remaining parsimonious. METHODS In total, 55 college students (n=6, 11% second-year students and n=49, 89% first-year students) volunteered to provide daily self-reports of perceived stress via a smartphone app and wore an actigraphy wristband for the estimation of daily sleep duration continuously throughout the academic year (median usable daily observations per participant: 178, IQR 65.5). The individual-level linear model, developed in a Bayesian framework, included the predictor and outcome of interest and a covariate for the day of the week to account for weekly patterns. We validated the model on the cohort of second-year students (n=6, used as a pilot sample) by applying it to variables expected to correlate positively within individuals: objective sleep duration and self-reported sleep quality. The model was then applied to the fully independent target sample of first-year students (n=49) for the examination of bidirectional associations between daily stress levels and sleep duration. RESULTS Proof-of-concept analyses captured expected associations between objective sleep duration and subjective sleep quality in every pilot participant. Target analyses revealed negative associations between sleep duration and perceived stress in most of the participants (45/49, 92%), but their temporal association varied. Of the 49 participants, 19 (39%) showed a significant association (probability of direction>0.975): 8 (16%) showed elevated stress in the day associated with shorter sleep later that night, 5 (10%) showed shorter sleep associated with elevated stress the next day, and 6 (12%) showed both directions of association. Of note, when analyzed using a group-based multilevel model, individual estimates were systematically attenuated, and some even reversed sign. CONCLUSIONS The dynamic interplay of stress and sleep in daily life is likely person specific. Paired with intensive longitudinal data, our individual-level linear model provides a precision framework for the estimation of stable real-world behavioral and psychological dynamics and may support the personalized prioritization of intervention targets for health and well-being.
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Affiliation(s)
- Constanza M Vidal Bustamante
- Department of Psychology, Harvard University, Cambridge, MA, United States
- Center for Brain Science, Harvard University, Cambridge, MA, United States
| | - Garth Coombs Iii
- Department of Psychology, Harvard University, Cambridge, MA, United States
- Center for Brain Science, Harvard University, Cambridge, MA, United States
| | - Habiballah Rahimi-Eichi
- Department of Psychology, Harvard University, Cambridge, MA, United States
- Center for Brain Science, Harvard University, Cambridge, MA, United States
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Patrick Mair
- Department of Psychology, Harvard University, Cambridge, MA, United States
| | - Jukka-Pekka Onnela
- Department of Biostatistics, Harvard University, Boston, MA, United States
| | - Justin T Baker
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Randy L Buckner
- Department of Psychology, Harvard University, Cambridge, MA, United States
- Center for Brain Science, Harvard University, Cambridge, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
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12
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Kurt I, Krauhausen I, Spolaor S, van de Burgt Y. Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks. Adv Sci (Weinh) 2024:e2308261. [PMID: 38682442 DOI: 10.1002/advs.202308261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/05/2024] [Indexed: 05/01/2024]
Abstract
Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial neural networks (ANNs) are showing promising results for reliable glucose predictions, offering timely warnings for glucose fluctuations. The translation of these software-based ANNs into dedicated computing hardware opens a route toward automated insulin delivery systems ultimately enhancing the quality of life for diabetic patients. ANNs are transforming this field, potentially leading to implantable smart prediction devices and ultimately to a fully artificial pancreas. However, this transition presents several challenges, including the need for specialized, compact, lightweight, and low-power hardware. Organic polymer-based electronics are a promising solution as they have the ability to implement the behavior of neural networks, operate at low voltage, and possess key attributes like flexibility, stretchability, and biocompatibility. Here, the study focuses on implementing software-based neural networks for glucose prediction into hardware systems. How to minimize network requirements, downscale the architecture, and integrate the neural network with electrochemical neuromorphic organic devices, meeting the strict demands of smart implants for in-body computation of glucose prediction is investigated.
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Affiliation(s)
- Ibrahim Kurt
- Microsystems, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, 5612 AE, The Netherlands
| | - Imke Krauhausen
- Microsystems, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, 5612 AE, The Netherlands
- Max Planck Institute for Polymer Research, 55128, Mainz, Germany
| | - Simone Spolaor
- Microsystems, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, 5612 AE, The Netherlands
| | - Yoeri van de Burgt
- Microsystems, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, 5612 AE, The Netherlands
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Shayne M, Molina LA, Hu B, Chomiak T. Implementing Gait Kinematic Trajectory Forecasting Models on an Embedded System. Sensors (Basel) 2024; 24:2649. [PMID: 38676266 PMCID: PMC11055148 DOI: 10.3390/s24082649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/21/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024]
Abstract
Smart algorithms for gait kinematic motion prediction in wearable assistive devices including prostheses, bionics, and exoskeletons can ensure safer and more effective device functionality. Although embedded systems can support the use of smart algorithms, there are important limitations associated with computational load. This poses a tangible barrier for models with increased complexity that demand substantial computational resources for superior performance. Forecasting through Recurrent Topology (FReT) represents a computationally lightweight time-series data forecasting algorithm with the ability to update and adapt to the input data structure that can predict complex dynamics. Here, we deployed FReT on an embedded system and evaluated its accuracy, computational time, and precision to forecast gait kinematics from lower-limb motion sensor data from fifteen subjects. FReT was compared to pretrained hyperparameter-optimized NNET and deep-NNET (D-NNET) model architectures, both with static model weight parameters and iteratively updated model weight parameters to enable adaptability to evolving data structures. We found that FReT was not only more accurate than all the network models, reducing the normalized root-mean-square error by almost half on average, but that it also provided the best balance between accuracy, computational time, and precision when considering the combination of these performance variables. The proposed FReT framework on an embedded system, with its improved performance, represents an important step towards the development of new sensor-aided technologies for assistive ambulatory devices.
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Affiliation(s)
- Madina Shayne
- Department of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
| | - Leonardo A. Molina
- CSM Optogenetics Platform, University of Calgary, 3330 Hospital Drive, Calgary, AB T2N 4N1, Canada;
| | - Bin Hu
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, AB T2N 4N1, Canada;
| | - Taylor Chomiak
- CSM Optogenetics Platform, University of Calgary, 3330 Hospital Drive, Calgary, AB T2N 4N1, Canada;
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, AB T2N 4N1, Canada;
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Alvarez-Romero C, Polo-Molina A, Sánchez-Úbeda EF, Jimenez-De-Juan C, Cuadri-Benitez MP, Rivas-Gonzalez JA, Portela J, Palacios R, Rodriguez-Morcillo C, Muñoz A, Parra-Calderon CL, Nieto-Martin MD, Ollero-Baturone M, Hernández-Quiles C. Machine Learning-Based Prediction of Changes in the Clinical Condition of Patients With Complex Chronic Diseases: 2-Phase Pilot Prospective Single-Center Observational Study. JMIR Form Res 2024; 8:e52344. [PMID: 38640473 PMCID: PMC11069093 DOI: 10.2196/52344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/18/2024] [Accepted: 02/19/2024] [Indexed: 04/21/2024] Open
Abstract
BACKGROUND Functional impairment is one of the most decisive prognostic factors in patients with complex chronic diseases. A more significant functional impairment indicates that the disease is progressing, which requires implementing diagnostic and therapeutic actions that stop the exacerbation of the disease. OBJECTIVE This study aimed to predict alterations in the clinical condition of patients with complex chronic diseases by predicting the Barthel Index (BI), to assess their clinical and functional status using an artificial intelligence model and data collected through an internet of things mobility device. METHODS A 2-phase pilot prospective single-center observational study was designed. During both phases, patients were recruited, and a wearable activity tracker was allocated to gather physical activity data. Patients were categorized into class A (BI≤20; total dependence), class B (2060; moderate or mild dependence, or independent). Data preprocessing and machine learning techniques were used to analyze mobility data. A decision tree was used to achieve a robust and interpretable model. To assess the quality of the predictions, several metrics including the mean absolute error, median absolute error, and root mean squared error were considered. Statistical analysis was performed using SPSS and Python for the machine learning modeling. RESULTS Overall, 90 patients with complex chronic diseases were included: 50 during phase 1 (class A: n=10; class B: n=20; and class C: n=20) and 40 during phase 2 (class B: n=20 and class C: n=20). Most patients (n=85, 94%) had a caregiver. The mean value of the BI was 58.31 (SD 24.5). Concerning mobility aids, 60% (n=52) of patients required no aids, whereas the others required walkers (n=18, 20%), wheelchairs (n=15, 17%), canes (n=4, 7%), and crutches (n=1, 1%). Regarding clinical complexity, 85% (n=76) met patient with polypathology criteria with a mean of 2.7 (SD 1.25) categories, 69% (n=61) met the frailty criteria, and 21% (n=19) met the patients with complex chronic diseases criteria. The most characteristic symptoms were dyspnea (n=73, 82%), chronic pain (n=63, 70%), asthenia (n=62, 68%), and anxiety (n=41, 46%). Polypharmacy was presented in 87% (n=78) of patients. The most important variables for predicting the BI were identified as the maximum step count during evening and morning periods and the absence of a mobility device. The model exhibited consistency in the median prediction error with a median absolute error close to 5 in the training, validation, and production-like test sets. The model accuracy for identifying the BI class was 91%, 88%, and 90% in the training, validation, and test sets, respectively. CONCLUSIONS Using commercially available mobility recording devices makes it possible to identify different mobility patterns and relate them to functional capacity in patients with polypathology according to the BI without using clinical parameters.
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Affiliation(s)
- Celia Alvarez-Romero
- Computational Health Informatics Group, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Consejo Superior de Investigaciones Científicas, University of, Seville, Spain
| | - Alejandro Polo-Molina
- Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
| | | | | | | | - Jose Antonio Rivas-Gonzalez
- Computational Health Informatics Group, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Consejo Superior de Investigaciones Científicas, University of, Seville, Spain
| | - Jose Portela
- Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
| | - Rafael Palacios
- Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
| | - Carlos Rodriguez-Morcillo
- Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
| | - Antonio Muñoz
- Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
| | - Carlos Luis Parra-Calderon
- Computational Health Informatics Group, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Consejo Superior de Investigaciones Científicas, University of, Seville, Spain
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Kuglics L, Géczy A, Dusek K, Busek D, Illés B. Personal Air-Quality Monitoring with Sensor-Based Wireless Internet-of-Things Electronics Embedded in Protective Face Masks. Sensors (Basel) 2024; 24:2601. [PMID: 38676218 PMCID: PMC11054044 DOI: 10.3390/s24082601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 04/10/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024]
Abstract
In this paper, the design and research of a sensor-based personal air-quality monitoring device are presented, which is retrofitted into different personal protective face masks. Due to its small size and low power consumption, the device can be integrated into and applied in practical urban usage. We present our research and the development of the sensor node based on a BME680-type environmental sensor cluster with a wireless IoT (Internet of Things)-capable central unit and overall low power consumption. The integration of the sensor node was investigated with traditional medical masks and a professional FFP2-type mask. The filtering efficiency after embedding was validated with a head model and a particle counter. We found that the professional mask withstood the embedding without losing the protective filtering aspect. We compared the inner and outer sensor data and investigated the temperature, pressure, humidity, and AQI (Air Quality Index) relations with possible sensor data-fusion options. The novelty is increased with the dual-sensor layout (inward and outward). It was found that efficient respiration monitoring is achievable with the device. With the analysis of the recorded data, characteristic signals were identified in an urban environment, enabling urban altimetry and urban zone detection. The results promote smart city concepts and help in endeavors related to SDGs (Sustainable Development Goals) 3 and 11.
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Affiliation(s)
- Lajos Kuglics
- Department of Electronics Technology, Faculty of Electronic Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
| | - Attila Géczy
- Department of Electronics Technology, Faculty of Electronic Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
- Department of Electrotechnology, Faculty of Electrical Engineering, Czech Technical University, 166 27 Prague, Czech Republic
| | - Karel Dusek
- Department of Electrotechnology, Faculty of Electrical Engineering, Czech Technical University, 166 27 Prague, Czech Republic
| | - David Busek
- Department of Electrotechnology, Faculty of Electrical Engineering, Czech Technical University, 166 27 Prague, Czech Republic
| | - Balázs Illés
- Department of Electronics Technology, Faculty of Electronic Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
- Łukasiewicz Research Network-Institute of Microelectronics and Photonics, LTCC Research Group, 02-255 Kraków, Poland
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Lyzwinski LN, Elgendi M, Menon C. Users' Acceptability and Perceived Efficacy of mHealth for Opioid Use Disorder: Scoping Review. JMIR Mhealth Uhealth 2024; 12:e49751. [PMID: 38602751 PMCID: PMC11046395 DOI: 10.2196/49751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 11/14/2023] [Accepted: 11/29/2023] [Indexed: 04/12/2024] Open
Abstract
BACKGROUND The opioid crisis continues to pose significant challenges to global public health, necessitating the development of novel interventions to support individuals in managing their substance use and preventing overdose-related deaths. Mobile health (mHealth), as a promising platform for addressing opioid use disorder, requires a comprehensive understanding of user perspectives to minimize barriers to care and optimize the benefits of mHealth interventions. OBJECTIVE This study aims to synthesize qualitative insights into opioid users' acceptability and perceived efficacy of mHealth and wearable technologies for opioid use disorder. METHODS A scoping review of PubMed (MEDLINE) and Google Scholar databases was conducted to identify research on opioid user perspectives concerning mHealth-assisted interventions, including wearable sensors, SMS text messaging, and app-based technology. RESULTS Overall, users demonstrate a high willingness to engage with mHealth interventions to prevent overdose-related deaths and manage opioid use. Users perceive mHealth as an opportunity to access care and desire the involvement of trusted health care professionals in these technologies. User comfort with wearing opioid sensors emerged as a significant factor. Personally tailored content, social support, and encouragement are preferred by users. Privacy concerns and limited access to technology pose barriers to care. CONCLUSIONS To maximize benefits and minimize risks for users, it is crucial to implement robust privacy measures, provide comprehensive user training, integrate behavior change techniques, offer professional and peer support, deliver tailored messages, incorporate behavior change theories, assess readiness for change, design stigma-reducing apps, use visual elements, and conduct user-focused research for effective opioid management in mHealth interventions. mHealth demonstrates considerable potential as a tool for addressing opioid use disorder and preventing overdose-related deaths, given the high acceptability and perceived benefits reported by users.
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Affiliation(s)
- Lynnette Nathalie Lyzwinski
- Menrva Research Group, School of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Vancouver, BC, Canada
| | - Mohamed Elgendi
- ETH Biomedical and Mobile Health Technology Lab, Zurich, Switzerland
| | - Carlo Menon
- Menrva Research Group, School of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Vancouver, BC, Canada
- ETH Biomedical and Mobile Health Technology Lab, Zurich, Switzerland
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Michaud M, Guérin A, Dejean de La Bâtie M, Bancel L, Oudre L, Tricot A. The Analytical Validity of Stride Detection and Gait Parameters Reconstruction Using the Ankle-Mounted Inertial Measurement Unit Syde ®. Sensors (Basel) 2024; 24:2413. [PMID: 38676029 PMCID: PMC11054238 DOI: 10.3390/s24082413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/04/2024] [Accepted: 04/07/2024] [Indexed: 04/28/2024]
Abstract
The increasing use of inertial measurement units (IMU) in biomedical sciences brings new possibilities for clinical research. The aim of this paper is to demonstrate the accuracy of the IMU-based wearable Syde® device, which allows day-long and remote continuous gait recording in comparison to a reference motion capture system. Twelve healthy subjects (age: 23.17 ± 2.04, height: 174.17 ± 6.46 cm) participated in a controlled environment data collection and performed a series of gait tasks with both systems attached to each ankle. A total of 2820 strides were analyzed. The results show a median absolute stride length error of 1.86 cm between the IMU-based wearable device reconstruction and the motion capture ground truth, with the 75th percentile at 3.24 cm. The median absolute stride horizontal velocity error was 1.56 cm/s, with the 75th percentile at 2.63 cm/s. With a measurement error to the reference system of less than 3 cm, we conclude that there is a valid physical recovery of stride length and horizontal velocity from data collected with the IMU-based wearable Syde® device.
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Affiliation(s)
- Mona Michaud
- Sysnav, 27200 Vernon, France; (M.M.); (A.G.); (L.B.)
- Université Paris Saclay, Université Paris Cité, ENS Paris Saclay, CNRS, SSA, INSERM, Centre Borelli, 91190 Gif-sur-Yvette, France
| | - Alexandre Guérin
- Sysnav, 27200 Vernon, France; (M.M.); (A.G.); (L.B.)
- DataShape, Inria Saclay Ile-de-France, 91120 Palaiseau, France
- Laboratoire de Mathématiques d’Orsay, Université Paris-Saclay, CNRS, 91405 Orsay, France
| | | | | | - Laurent Oudre
- Université Paris Saclay, Université Paris Cité, ENS Paris Saclay, CNRS, SSA, INSERM, Centre Borelli, 91190 Gif-sur-Yvette, France
| | - Alexis Tricot
- Sysnav, 27200 Vernon, France; (M.M.); (A.G.); (L.B.)
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Konno S, Kudo H. Fundamental Study of a Wristwatch Sweat Lactic Acid Monitor. Biosensors (Basel) 2024; 14:187. [PMID: 38667180 PMCID: PMC11048019 DOI: 10.3390/bios14040187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 04/06/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024]
Abstract
A lactic acid (LA) monitoring system aimed at sweat monitoring was fabricated and tested. The sweat LA monitoring system uses a continuous flow of phosphate buffer saline, instead of chambers or cells, for collecting and storing sweat fluid excreted at the skin surface. To facilitate the use of the sweat LA monitoring system by subjects when exercising, the fluid control system, including the sweat sampling device, was designed to be unaffected by body movements or muscle deformation. An advantage of our system is that the skin surface condition is constantly refreshed by continuous flow. A real sample test was carried out during stationary bike exercise, which showed that LA secretion increased by approximately 10 μg/cm2/min compared to the baseline levels before exercise. The LA levels recovered to baseline levels after exercise due to the effect of continuous flow. This indicates that the wristwatch sweat LA monitor has the potential to enable a detailed understanding of the LA distribution at the skin surface.
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Affiliation(s)
| | - Hiroyuki Kudo
- Department of Electronics and Bioinformatics, School of Science and Technology, Meiji University, Tokyo 214-8571, Kanagawa, Japan
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Rauf S, Bilal RM, Li J, Vaseem M, Ahmad AN, Shamim A. Fully Screen-Printed and Gentle-to-Skin Wet ECG Electrodes with Compact Wireless Readout for Cardiac Diagnosis and Remote Monitoring. ACS Nano 2024; 18:10074-10087. [PMID: 38526458 PMCID: PMC11022287 DOI: 10.1021/acsnano.3c12477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 03/21/2024] [Accepted: 03/21/2024] [Indexed: 03/26/2024]
Abstract
Recent advances in electrocardiogram (ECG) diagnosis and monitoring have triggered a demand for smart and wearable ECG electrodes and readout systems. Here, we report the development of a fully screen-printed gentle-to-skin wet ECG electrode integrated with a scaled-down printed circuit board (PCB) packaged inside a 3D-printed antenna-on-package (AoP). All three components of the wet ECG electrode (i.e., silver nanowire-based conductive part, electrode gel, and adhesive gel) are screen-printed on a flexible plastic substrate and only require 265 times less metal for the conductive part and 176 times less ECG electrode gel than the standard commercial wet ECG electrodes. In addition, our electrically small AoP achieved a maximum read range of 142 m and offers a 4 times larger wireless communication range than the typical commercial chip antenna. The adult volunteers' study results indicated that our system recorded ECG data that correlated well with data from a commercial ECG system and electrodes. Furthermore, in the context of a 12-lead ECG diagnostic system, the fully printed wet ECG electrodes demonstrated a performance similar to that of commercially available wet ECG electrodes while being gentle on the skin. This was confirmed through a blind review method by two cardiology consultants and one family medicine consultant, validating the consistency of the diagnostic information obtained from both electrodes. In conclusion, these findings highlight the potential of fully screen-printed wet ECG electrodes for both monitoring and diagnostic purposes. These electrodes could serve as potential candidates for clinical practice, and the screen-printing method has the capability to facilitate industrial mass production.
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Affiliation(s)
- Sakandar Rauf
- Electrical
and Computer Engineering, CEMSE, King Abdullah
University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Rana M. Bilal
- Electrical
and Computer Engineering, CEMSE, King Abdullah
University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Jiajun Li
- Electrical
and Computer Engineering, CEMSE, King Abdullah
University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Mohammad Vaseem
- Electrical
and Computer Engineering, CEMSE, King Abdullah
University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Adeel N. Ahmad
- School
of Medicine, University of Nottingham, Nottingham NG7 2UH, United Kingdom
| | - Atif Shamim
- Electrical
and Computer Engineering, CEMSE, King Abdullah
University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
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20
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Yoo RM, Viggiano BT, Pundi KN, Fries JA, Zahedivash A, Podchiyska T, Din N, Shah NH. Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study. JMIR Med Inform 2024; 12:e51171. [PMID: 38596848 PMCID: PMC11024395 DOI: 10.2196/51171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 01/15/2024] [Accepted: 02/04/2024] [Indexed: 04/11/2024] Open
Abstract
Background With the capability to render prediagnoses, consumer wearables have the potential to affect subsequent diagnoses and the level of care in the health care delivery setting. Despite this, postmarket surveillance of consumer wearables has been hindered by the lack of codified terms in electronic health records (EHRs) to capture wearable use. Objective We sought to develop a weak supervision-based approach to demonstrate the feasibility and efficacy of EHR-based postmarket surveillance on consumer wearables that render atrial fibrillation (AF) prediagnoses. Methods We applied data programming, where labeling heuristics are expressed as code-based labeling functions, to detect incidents of AF prediagnoses. A labeler model was then derived from the predictions of the labeling functions using the Snorkel framework. The labeler model was applied to clinical notes to probabilistically label them, and the labeled notes were then used as a training set to fine-tune a classifier called Clinical-Longformer. The resulting classifier identified patients with an AF prediagnosis. A retrospective cohort study was conducted, where the baseline characteristics and subsequent care patterns of patients identified by the classifier were compared against those who did not receive a prediagnosis. Results The labeler model derived from the labeling functions showed high accuracy (0.92; F1-score=0.77) on the training set. The classifier trained on the probabilistically labeled notes accurately identified patients with an AF prediagnosis (0.95; F1-score=0.83). The cohort study conducted using the constructed system carried enough statistical power to verify the key findings of the Apple Heart Study, which enrolled a much larger number of participants, where patients who received a prediagnosis tended to be older, male, and White with higher CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes, stroke, vascular disease, age 65-74 years, sex category) scores (P<.001). We also made a novel discovery that patients with a prediagnosis were more likely to use anticoagulants (525/1037, 50.63% vs 5936/16,560, 35.85%) and have an eventual AF diagnosis (305/1037, 29.41% vs 262/16,560, 1.58%). At the index diagnosis, the existence of a prediagnosis did not distinguish patients based on clinical characteristics, but did correlate with anticoagulant prescription (P=.004 for apixaban and P=.01 for rivaroxaban). Conclusions Our work establishes the feasibility and efficacy of an EHR-based surveillance system for consumer wearables that render AF prediagnoses. Further work is necessary to generalize these findings for patient populations at other sites.
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Affiliation(s)
- Richard M Yoo
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, United States
| | - Ben T Viggiano
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, United States
| | - Krishna N Pundi
- Department of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, United States
| | - Jason A Fries
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, United States
| | - Aydin Zahedivash
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA, United States
| | - Tanya Podchiyska
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, United States
| | - Natasha Din
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, United States
| | - Nigam H Shah
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, United States
- Clinical Excellence Research Center, School of Medicine, Stanford University, Stanford, CA, United States
- Technology and Digital Services, Stanford Health Care, Stanford, CA, United States
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21
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Chimatapu SN, Mittelman SD, Habib M, Osuna-Garcia A, Vidmar AP. Wearable Devices Beyond Activity Trackers in Youth With Obesity: Summary of Options. Child Obes 2024; 20:208-218. [PMID: 37023409 PMCID: PMC10979694 DOI: 10.1089/chi.2023.0005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
Background: Current treatment protocols to prevent and treat pediatric obesity focus on prescriptive lifestyle interventions. However, treatment outcomes are modest due to poor adherence and heterogeneity in responses. Wearable technologies offer a unique solution as they provide real-time biofeedback that could improve adherence to and sustainability of lifestyle interventions. To date, all reviews on wearable devices in pediatric obesity cohorts have only explored biofeedback from physical activity trackers. Hence, we conducted a scoping review to (1) catalog other biofeedback wearable devices available in this cohort, (2) document various metrics collected from these devices, and (3) assess safety and adherence to these devices. Methods: This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Fifteen eligible studies examined the use of biofeedback wearable devices beyond activity trackers in pediatric cohorts, with an emphasis on feasibility of these devices. Results: Included studies varied in sample sizes (15-203) and in ages 6-21 years. Wearable devices are being used to capture various metrics of multicomponent weight loss interventions to provide more insights about glycemic variability, cardiometabolic function, sleep, nutrition, and body fat percentage. High safety and adherence rates were reported among these devices. Conclusions: Available evidence suggests that wearable devices have several applications aside from activity tracking, which could modify health behaviors through real-time biofeedback. Overall, these devices appear to be safe and feasible so as to be employed in various settings in the pediatric age group to prevent and treat obesity.
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Affiliation(s)
- Sri Nikhita Chimatapu
- Division of Endocrinology, Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Steven D. Mittelman
- Division of Endocrinology, Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Manal Habib
- Division of Endocrinology, Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Antonia Osuna-Garcia
- Department of Health and Life Sciences Librarian, Nursing, Biomedical Library, University of California Los Angeles, Los Angeles, CA, USA
| | - Alaina P. Vidmar
- Center for Endocrinology, Diabetes, and Metabolism, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
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Lin Y, Shull PB, Chossat JB. Design of a Wearable Real-Time Hand Motion Tracking System Using an Array of Soft Polymer Acoustic Waveguides. Soft Robot 2024; 11:282-295. [PMID: 37870761 DOI: 10.1089/soro.2022.0091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2023] Open
Abstract
Robust hand motion tracking holds promise for improved human-machine interaction in diverse fields, including virtual reality, and automated sign language translation. However, current wearable hand motion tracking approaches are typically limited in detection performance, wearability, and durability. This article presents a hand motion tracking system using multiple soft polymer acoustic waveguides (SPAWs). The innovative use of SPAWs as strain sensors offers several advantages that address the limitations. SPAWs are easily manufactured by casting a soft polymer shaped as a soft acoustic waveguide and containing a commercially available small ceramic piezoelectric transducer. When used as strain sensors, SPAWs demonstrate high stretchability (up to 100%), high linearity (R2 > 0.996 in all quasi-static, dynamic, and durability tensile tests), negligible hysteresis (<0.7410% under strain of up to 100%), excellent repeatability, and outstanding durability (up to 100,000 cycles). SPAWs also show high accuracy for continuous finger angle estimation (average root-mean-square errors [RMSE] <2.00°) at various flexion-extension speeds. Finally, a hand-tracking system is designed based on a SPAW array. An example application is developed to demonstrate the performance of SPAWs in real-time hand motion tracking in a three-dimensional (3D) virtual environment. To our knowledge, the system detailed in this article is the first to use soft acoustic waveguides to capture human motion. This work is part of an ongoing effort to develop soft sensors using both time and frequency domains, with the goal of extracting decoupled signals from simple sensing structures. As such, it represents a novel and promising path toward soft, simple, and wearable multimodal sensors.
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Affiliation(s)
- Yuan Lin
- Robotics Institute, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Peter B Shull
- Robotics Institute, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jean-Baptiste Chossat
- Soft Transducers Laboratory, École Polytechnique Fédérale de Lausanne, Neuchâtel, Switzerland
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23
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Kang F, Shan J, Li Z, Liu Y, Ye J, Zhang X, Liu C, Wang F. [Development of Wireless Wearable Sleep Monitoring System Based on EEG Signal]. Zhongguo Yi Liao Qi Xie Za Zhi 2024; 48:173-178. [PMID: 38605617 DOI: 10.12455/j.issn.1671-7104.230414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
A wireless wearable sleep monitoring system based on EEG signals is developed. The collected EEG signals are wirelessly sent to the PC or mobile phone Bluetooth APP for real-time display. The system is small in size, low in power consumption, and light in weight. It can be worn on the patient's forehead and is comfortable. It can be applied to home sleep monitoring scenarios and has good application value. The key performance indicators of the system are compared with the industry-related medical device measurement standards, and the measurement results are better than the special standards.
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Affiliation(s)
- Fuhao Kang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518052
| | - Jieying Shan
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518052
| | - Zexi Li
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518052
| | - Yanan Liu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518052
| | - Jilun Ye
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518052
- Shenzhen Weituoli Medical Electronics Co., Ltd., Shenzhen, 518107
- Guangdong BIOLIGHT Innovation Research Institute, Zhuhai, 519080
| | - Xu Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518052
| | - Chunsheng Liu
- Shenzhen Weituoli Medical Electronics Co., Ltd., Shenzhen, 518107
| | - Fan Wang
- Shenzhen Weituoli Medical Electronics Co., Ltd., Shenzhen, 518107
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Mereu F, Cordella F, Paolini R, Scarpelli A, Demofonti A, Zollo L, Gruppioni E. A Sensory Feedback Neural Stimulator Prototype for Both Implantable and Wearable Applications. Micromachines (Basel) 2024; 15:480. [PMID: 38675291 PMCID: PMC11051761 DOI: 10.3390/mi15040480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/23/2024] [Accepted: 03/29/2024] [Indexed: 04/28/2024]
Abstract
The restoration of sensory feedback is one of the current challenges in the field of prosthetics. This work, following the analysis of the various types of sensory feedback, aims to present a prototype device that could be used both for implantable applications to perform PNS and for wearable applications, performing TENS, to restore sensory feedback. The two systems are composed of three electronic boards that are presented in detail, as well as the bench tests carried out. To the authors' best knowledge, this work presents the first device that can be used in a dual scenario for restoring sensory feedback. Both the implantable and wearable versions respected the expected values regarding the stimulation parameters. In its implantable version, the proposed system allows simultaneous and independent stimulation of 30 channels. Furthermore, the capacity of the wearable version to elicit somatic sensations was evaluated on healthy participants demonstrating performance comparable with commercial solutions.
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Affiliation(s)
- Federico Mereu
- Centro Protesi Inail, Vigorso di Budrio, 40054 Bologna, Italy;
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Francesca Cordella
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Roberto Paolini
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Alessia Scarpelli
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Andrea Demofonti
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Loredana Zollo
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
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25
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Miqueleiz U, Aguado-Jimenez R, Lecumberri P, Garcia-Tabar I, Gorostiaga EM. Reliability of Xsens inertial measurement unit in measuring trunk accelerations: a sex-based differences study during incremental treadmill running. Front Sports Act Living 2024; 6:1357353. [PMID: 38600906 PMCID: PMC11004309 DOI: 10.3389/fspor.2024.1357353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/11/2024] [Indexed: 04/12/2024] Open
Abstract
Introduction Inertial measurement units (IMUs) are utilized to measure trunk acceleration variables related to both running performances and rehabilitation purposes. This study examined both the reliability and sex-based differences of these variables during an incremental treadmill running test. Methods Eighteen endurance runners performed a test-retest on different days, and 30 runners (15 females) were recruited to analyze sex-based differences. Mediolateral (ML) and vertical (VT) trunk displacement and root mean square (RMS) accelerations were analyzed at 9, 15, and 21 km·h-1. Results No significant differences were found between test-retests [effect size (ES)<0.50)]. Higher intraclass correlation coefficients (ICCs) were found in the trunk displacement (0.85-0.96) compared to the RMS-based variables (0.71-0.94). Male runners showed greater VT displacement (ES = 0.90-1.0), while female runners displayed greater ML displacement, RMS ML and anteroposterior (AP), and resultant euclidean scalar (RES) (ES = 0.83-1.9). Discussion The IMU was found reliable for the analysis of the studied trunk acceleration-based variables. This is the first study that reports different results concerning acceleration (RMS) and trunk displacement variables for a same axis in the analysis of sex-based differences.
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Affiliation(s)
- Unai Miqueleiz
- Department of Health Sciences, Public University of Navarra, Pamplona, Spain
- Studies, Research and Sports Medicine Centre (CEIMD), Government of Navarre, Pamplona, Spain
| | | | - Pablo Lecumberri
- Department of Mathematics, Public University of Navarre, Pamplona, Spain
| | - Ibai Garcia-Tabar
- Society, Sports and Physical Exercise Research Group (GIKAFIT), Department of Physical Education and Sport, Faculty of Education and Sport, University of the Basque Country, Vitoria-Gasteiz, Spain
| | - Esteban M. Gorostiaga
- Studies, Research and Sports Medicine Centre (CEIMD), Government of Navarre, Pamplona, Spain
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Gabb VG, Blackman J, Morrison HD, Biswas B, Li H, Turner N, Russell GM, Greenwood R, Jolly A, Trender W, Hampshire A, Whone A, Coulthard E. Remote Evaluation of Sleep and Circadian Rhythms in Older Adults With Mild Cognitive Impairment and Dementia: Protocol for a Feasibility and Acceptability Mixed Methods Study. JMIR Res Protoc 2024; 13:e52652. [PMID: 38517469 PMCID: PMC10998181 DOI: 10.2196/52652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 02/12/2024] [Accepted: 02/13/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Sleep disturbances are a potentially modifiable risk factor for neurodegenerative dementia secondary to Alzheimer disease (AD) and Lewy body disease (LBD). Therefore, we need to identify the best methods to study sleep in this population. OBJECTIVE This study will assess the feasibility and acceptability of various wearable devices, smart devices, and remote study tasks in sleep and cognition research for people with AD and LBD. METHODS We will deliver a feasibility and acceptability study alongside a prospective observational cohort study assessing sleep and cognition longitudinally in the home environment. Adults aged older than 50 years who were diagnosed with mild to moderate dementia or mild cognitive impairment (MCI) due to probable AD or LBD and age-matched controls will be eligible. Exclusion criteria include lack of capacity to consent to research, other causes of MCI or dementia, and clinically significant sleep disorders. Participants will complete a cognitive assessment and questionnaires with a researcher and receive training and instructions for at-home study tasks across 8 weeks. At-home study tasks include remote sleep assessments using wearable devices (electroencephalography headband and actigraphy watch), app-based sleep diaries, online cognitive assessments, and saliva samples for melatonin- and cortisol-derived circadian markers. Feasibility outcomes will be assessed relating to recruitment and retention, data completeness, data quality, and support required. Feedback on acceptability and usability will be collected throughout the study period and end-of-study interviews will be analyzed using thematic analysis. RESULTS Recruitment started in February 2022. Data collection is ongoing, with final data expected in February 2024 and data analysis and publication of findings scheduled for the summer of 2024. CONCLUSIONS This study will allow us to assess if remote testing using smart devices and wearable technology is a viable alternative to traditional sleep measurements, such as polysomnography and questionnaires, in older adults with and without MCI or dementia due to AD or LBD. Understanding participant experience and the barriers and facilitators to technology use for research purposes and remote research in this population will assist with the development of, recruitment to, and retention within future research projects studying sleep and cognition outside of the clinic or laboratory. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/52652.
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Affiliation(s)
- Victoria Grace Gabb
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom
| | - Jonathan Blackman
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom
| | - Hamish Duncan Morrison
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom
| | - Bijetri Biswas
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Haoxuan Li
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom
- King's College Hospital, King's College Hospital NHS Foundation Trust, London, United Kingdom
- Bristol Royal Infirmary, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom
| | - Nicholas Turner
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | | | - Rosemary Greenwood
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Research & Innovation, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom
| | - Amy Jolly
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom
- UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - William Trender
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Adam Hampshire
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Alan Whone
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom
| | - Elizabeth Coulthard
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Neurology Department, Bristol Brain Centre, North Bristol NHS Trust, Bristol, United Kingdom
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Ahn HJ, Choi EK, Lee SR, Kwon S, Song HS, Lee YS, Oh S. Three-Day Monitoring of Adhesive Single-Lead Electrocardiogram Patch for Premature Ventricular Complex: Prospective Study for Diagnosis Validation and Evaluation of Burden Fluctuation. J Med Internet Res 2024; 26:e46098. [PMID: 38512332 PMCID: PMC10995782 DOI: 10.2196/46098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 08/13/2023] [Accepted: 02/12/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND Wearable electrocardiogram (ECG) monitoring devices are used worldwide. However, data on the diagnostic yield of an adhesive single-lead ECG patch (SEP) to detect premature ventricular complex (PVC) and the optimal duration of wearing an SEP for PVC burden assessment are limited. OBJECTIVE We aimed to validate the diagnostic yield of an SEP (mobiCARE MC-100, Seers Technology) for PVC detection and evaluate the PVC burden variation recorded by the SEP over a 3-day monitoring period. METHODS This is a prospective study of patients with documented PVC on a 12-lead ECG. Patients underwent simultaneous ECG monitoring with the 24-hour Holter monitor and SEP on the first day. On the subsequent second and third days, ECG monitoring was continued using only SEP, and a 3-day extended monitoring was completed. The diagnostic yield of SEP for PVC detection was evaluated by comparison with the results obtained on the first day of Holter monitoring. The PVC burden monitored by SEP for 3 days was used to assess the daily and 6-hour PVC burden variations. The number of patients additionally identified to reach PVC thresholds of 10%, 15%, and 20% during the 3-day extended monitoring by SEP and the clinical factors associated with the higher PVC burden variations were explored. RESULTS The recruited data of 134 monitored patients (mean age, 54.6 years; males, 45/134, 33.6%) were analyzed. The median daily PVC burden of these patients was 2.4% (IQR 0.2%-10.9%), as measured by the Holter monitor, and 3.3% (IQR 0.3%-11.7%), as measured in the 3-day monitoring by SEP. The daily PVC burden detected on the first day of SEP was in agreement with that of the Holter monitor: the mean difference was -0.07%, with 95% limits of agreement of -1.44% to 1.30%. A higher PVC burden on the first day was correlated with a higher daily (R2=0.34) and 6-hour burden variation (R2=0.48). Three-day monitoring by SEP identified 29% (12/42), 18% (10/56), and 7% (4/60) more patients reaching 10%, 15%, and 20% of daily PVC burden, respectively. Younger age was additionally associated with the identification of clinically significant PVC burden during the extended monitoring period (P=.02). CONCLUSIONS We found that the mobiCARE MC-100 SEP accurately detects PVC with comparable diagnostic yield to the 24-hour Holter monitor. Performing 3-day PVC monitoring with SEP, especially among younger patients, may offer a pragmatic alternative for identifying more individuals exceeding the clinically significant PVC burden threshold.
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Affiliation(s)
- Hyo-Jeong Ahn
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eue-Keun Choi
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - So-Ryoung Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soonil Kwon
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hee-Seok Song
- Seers Technology Co, Ltd, Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Young-Shin Lee
- Seers Technology Co, Ltd, Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Seil Oh
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
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Yamamoto A, Yamada E, Ibara T, Nihey F, Inai T, Tsukamoto K, Waki T, Yoshii T, Kobayashi Y, Nakahara K, Fujita K. Using In-Shoe Inertial Measurement Unit Sensors to Understand Daily-Life Gait Characteristics in Patients With Distal Radius Fractures During 6 Months of Recovery: Cross-Sectional Study. JMIR Mhealth Uhealth 2024; 12:e55178. [PMID: 38506913 PMCID: PMC10993120 DOI: 10.2196/55178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/29/2024] [Accepted: 02/26/2024] [Indexed: 03/21/2024] Open
Abstract
BACKGROUND A distal radius fracture (DRF) is a common initial fragility fracture among women in their early postmenopausal period, which is associated with an increased risk of subsequent fractures. Gait assessments are valuable for evaluating fracture risk; inertial measurement units (IMUs) have been widely used to assess gait under free-living conditions. However, little is known about long-term changes in patients with DRF, especially concerning daily-life gait. We hypothesized that, in the long term, the daily-life gait parameters in patients with DRF could enable us to reveal future risk factors for falls and fractures. OBJECTIVE This study assessed the spatiotemporal characteristics of patients with DRF at 4 weeks and 6 months of recovery. METHODS We recruited 16 women in their postmenopausal period with DRF as their first fragility fracture (mean age 62.3, SD 7.0 years) and 28 matched healthy controls (mean age 65.6, SD 8.0 years). Daily-life gait assessments and physical assessments, such as hand grip strength (HGS), were performed using an in-shoe IMU sensor. Participants' results were compared with those of the control group, and their recovery was assessed for 6 months after the fracture. RESULTS In the fracture group, at 4 weeks after DRF, lower foot height in the swing phase (P=.049) and higher variability of stride length (P=.03) were observed, which improved gradually. However, the dorsiflexion angle in the fracture group tended to be lower consistently during 6 months (at 4 weeks: P=.06; during 6 months: P=.07). As for the physical assessments, the fracture group showed lower HGS at all time points (at 4 weeks: P<.001; during 6 months: P=.04), despite significant improvement at 6 months (P<.001). CONCLUSIONS With an in-shoe IMU sensor, we discovered the recovery of spatiotemporal gait characteristics 6 months after DRF surgery without the participants' awareness. The consistently unchanged dorsiflexion angle in the swing phase and lower HGS could be associated with fracture risk, implying the high clinical importance of appropriate interventions for patients with DRF to prevent future fractures. These results could be applied to a screening tool for evaluating the risk of falls and fractures, which may contribute to constructing a new health care system using wearable devices in the near future.
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Affiliation(s)
- Akiko Yamamoto
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Eriku Yamada
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Takuya Ibara
- Department of Functional Joint Anatomy, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Fumiyuki Nihey
- Biometrics Research Laboratories, NEC Corporation, Chiba, Japan
| | - Takuma Inai
- Biomechanics and Exercise Physiology Research Group, Health and Medical Research Institute, Department of Life Science and Technology, National Institute of Advanced Industrial Science and Technology, Kagawa, Japan
| | - Kazuya Tsukamoto
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Tomohiko Waki
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Toshitaka Yoshii
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yoshiyuki Kobayashi
- Human Augmentation Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
| | | | - Koji Fujita
- Department of Functional Joint Anatomy, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
- Division of Medical Design Innovations, Open Innovation Center, Institute of Research Innovation, Tokyo Medical and Dental University, Tokyo, Japan
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Sieber C, Haag C, Polhemus A, Haile SR, Sylvester R, Kool J, Gonzenbach R, von Wyl V. Exploring the Major Barriers to Physical Activity in Persons With Multiple Sclerosis: Observational Longitudinal Study. JMIR Rehabil Assist Technol 2024; 11:e52733. [PMID: 38498024 PMCID: PMC10985607 DOI: 10.2196/52733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/21/2023] [Accepted: 02/02/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Physical activity (PA) represents a low-cost and readily available means of mitigating multiple sclerosis (MS) symptoms and alleviating the disease course. Nevertheless, persons with MS engage in lower levels of PA than the general population. OBJECTIVE This study aims to enhance the understanding of the barriers to PA engagement in persons with MS and to evaluate the applicability of the Barriers to Health Promoting Activities for Disabled Persons (BHADP) scale for assessing barriers to PA in persons with MS, by comparing the BHADP score with self-reported outcomes of fatigue, depression, self-efficacy, and health-related quality of life, as well as sensor-measured PA. METHODS Study participants (n=45; median age 46, IQR 40-51 years; median Expanded Disability Status Scale score 4.5, IQR 3.5-6) were recruited among persons with MS attending inpatient neurorehabilitation. They wore a Fitbit Inspire HR (Fitbit Inc) throughout their stay at the rehabilitation clinic (phase 1; 2-4 wk) and for the 4 following weeks at home (phase 2; 4 wk). Sensor-based step counts and cumulative minutes in moderate to vigorous PA were computed for the last 7 days at the clinic and at home. On the basis of PA during the last 7 end-of-study days, we grouped the study participants as active (≥10,000 steps/d) and less active (<10,000 steps/d) to explore PA barriers compared with PA level. PA barriers were repeatedly assessed through the BHADP scale. We described the relevance of the 18 barriers of the BHADP scale assessed at the end of the study and quantified their correlations with the Spearman correlation test. We evaluated the associations of the BHADP score with end-of-study reported outcomes of fatigue, depression, self-efficacy, and health-related quality of life with multivariable regression models. We performed separate regression analyses to examine the association of the BHADP score with different sensor-measured outcomes of PA. RESULTS The less active group reported higher scores for the BHADP items Feeling what I do doesn't help, No one to help me, and Lack of support from family/friends. The BHADP items Not interested in PA and Impairment were positively correlated. The BHADP score was positively associated with measures of fatigue and depression and negatively associated with self-efficacy and health-related quality of life. The BHADP score showed an inverse relationship with the level of PA measured but not when dichotomized according to the recommended PA level thresholds. CONCLUSIONS The BHADP scale is a valid and well-adapted tool for persons with MS because it reflects common MS symptoms such as fatigue and depression, as well as self-efficacy and health-related quality of life. Moreover, decreases in PA levels are often related to increases in specific barriers in the lives of persons with MS and should hence be addressed jointly in health care management.
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Affiliation(s)
- Chloé Sieber
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Christina Haag
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Ashley Polhemus
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Sarah R Haile
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | | | - Jan Kool
- Valens Rehabilitation Centre, Valens, Switzerland
| | | | - Viktor von Wyl
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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Podda J, Pedullà L, Brichetto G, Tacchino A. Evaluating Cognitive-Motor Interference in Multiple Sclerosis: A Technology-Based Approach. Bioengineering (Basel) 2024; 11:277. [PMID: 38534551 DOI: 10.3390/bioengineering11030277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/06/2024] [Accepted: 03/12/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND People with multiple sclerosis (PwMS) frequently present both cognitive and motor impairments, so it is reasonable to assume they may have difficulties in executing dual-tasks (DT). The aim of the present study is to identify novel technology-based parameters to assess cognitive-motor interference (CMI) in PwMS. In particular, we focused on the definition of dual-task cost (DTC) measures using wearable and portable tools such as insoles and mobile apps. METHODS All participants underwent a verbal fluency task (cognitive single-task, ST), a motor ST of walking, and a combination of these tasks (DT). Number of words uttered in the cognitive ST and steps recorded by insoles were used to calculate the motor and cognitive DTC. RESULTS The number of steps strongly correlated with the walked meters for both single- (r = 0.88, p < 0.05) and dual- (r = 0.91, p < 0.05) tasks. Motor but not cognitive performances significantly worsened during DT. Over the cognitive ST and DT, the number of pronounced words progressively decreased, probably due to the activation of different cognitive processes. Cognitive efforts could be the cause of cognitive task prioritization. CONCLUSIONS Our findings promote the use of low-cost devices to assess CMI easily in the clinical context and to detect ecologically valid DT impairments.
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Affiliation(s)
- Jessica Podda
- Scientific Research Area, Italian Multiple Sclerosis Foundation, 16149 Genoa, Italy
| | - Ludovico Pedullà
- Scientific Research Area, Italian Multiple Sclerosis Foundation, 16149 Genoa, Italy
| | - Giampaolo Brichetto
- Scientific Research Area, Italian Multiple Sclerosis Foundation, 16149 Genoa, Italy
- AISM Rehabilitation Service of Genoa, Italian Multiple Sclerosis Society, 16149 Genoa, Italy
| | - Andrea Tacchino
- Scientific Research Area, Italian Multiple Sclerosis Foundation, 16149 Genoa, Italy
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Triana AM, Saramäki J, Glerean E, Hayward NMEA. Neuroscience meets behavior: A systematic literature review on magnetic resonance imaging of the brain combined with real-world digital phenotyping. Hum Brain Mapp 2024; 45:e26620. [PMID: 38436603 PMCID: PMC10911114 DOI: 10.1002/hbm.26620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 03/05/2024] Open
Abstract
A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.
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Affiliation(s)
- Ana María Triana
- Department of Computer Science, School of ScienceAalto UniversityEspooFinland
| | - Jari Saramäki
- Department of Computer Science, School of ScienceAalto UniversityEspooFinland
| | - Enrico Glerean
- Department of Neuroscience and Biomedical Engineering, School of ScienceAalto UniversityEspooFinland
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Keogh A, Brennan C, Johnston W, Dickson J, Leslie SJ, Burke D, Megyesi P, Caulfield B. Six-Month Pilot Testing of a Digital Health Tool to Support Effective Self-Care in People With Heart Failure: Mixed Methods Study. JMIR Form Res 2024; 8:e52442. [PMID: 38427410 PMCID: PMC10959238 DOI: 10.2196/52442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/26/2023] [Accepted: 11/22/2023] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Digital tools may support people to self-manage their heart failure (HF). Having previously outlined the human-centered design development of a digital tool to support self-care of HF, the next step was to pilot the tool over a period of time to establish people's acceptance of it in practice. OBJECTIVE This study aims to conduct an observational pilot study to examine the usability, adherence, and feasibility of a digital health tool for HF within the Irish health care system. METHODS A total of 19 participants with HF were provided with a digital tool comprising a mobile app and the Fitbit Charge 4 and Aria Air smart scales for a period of 6 months. Changes to their self-care were assessed before and after the study with the 9-item European HF Self-care Behavior Scale (EHFScBS) and the Minnesota Living with HF Questionnaire (MLwHFQ) using a Wilcoxon signed rank test. After the study, 3 usability questionnaires were implemented and descriptively analyzed: the System Usability Scale (SUS), Wearable Technology Motivation Scale (WTMS), and Comfort Rating Scale (CRS). Participants also undertook a semistructured interview regarding their experiences with the digital tool. Interviews were analyzed deductively using the Theoretical Domains Framework. RESULTS Participants wore their devices for an average of 86.2% of the days in the 6-month testing period ranging from 40.6% to 98%. Although improvements in the EHFScBS and MLwHFQ were seen, these changes were not significant (P=.10 and P=.70, respectively, where P>.03, after a Bonferroni correction). SUS results suggest that the usability of this system was not acceptable with a median score of 58.8 (IQR 55.0-60.0; range 45.0-67.5). Participants demonstrated a strong motivation to use the system according to the WTMS (median 6.0, IQR 5.0-7.0; range 1.0-7.0), whereas the Fitbit was considered very comfortable as demonstrated by the low CRS results (median 0.0, IQR 0.0-0.0; range 0.0-2.0). According to participant interviews, the digital tool supported self-management through increased knowledge, improved awareness, decision-making, and confidence in their own data, and improving their social support through a feeling of comfort in being watched. CONCLUSIONS The digital health tool demonstrated high levels of adherence and acceptance among participants. Although the SUS results suggest low usability, this may be explained by participants uncertainty that they were using it fully, rather than it being unusable, especially given the experiences documented in their interviews. The digital tool targeted key self-management behaviors and feelings of social support. However, a number of changes to the tool, and the health service, are required before it can be implemented at scale. A full-scale feasibility trial conducted at a wider level is required to fully determine its potential effectiveness and wider implementation needs.
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Affiliation(s)
- Alison Keogh
- Insight Centre Data Analytics, University College Dublin, Dublin, Ireland
- School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Carol Brennan
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland
| | - William Johnston
- Insight Centre Data Analytics, University College Dublin, Dublin, Ireland
| | - Jane Dickson
- Physiotherapy Department, Beacon Hospital, Dublin, Ireland
- Cardiology, Beacon Hospital, Dublin, Ireland
| | | | - David Burke
- Cardiology, Beacon Hospital, Dublin, Ireland
- School of Medicine, University College Dublin, Dublin, Ireland
| | - Peter Megyesi
- Insight Centre Data Analytics, University College Dublin, Dublin, Ireland
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland
| | - Brian Caulfield
- Insight Centre Data Analytics, University College Dublin, Dublin, Ireland
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland
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Yilmaz M, Yusuf A, Gurkan K, Ballikaya S. Developing High-Performance and Low-Cost Paint Thermoelectric Materials for Low-Midtemperature Applications. ACS Appl Mater Interfaces 2024. [PMID: 38427785 DOI: 10.1021/acsami.3c19309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Abstract
Most thermoelectric (TE) materials used to convert heat energy into electrical energy are expensive and, to a certain degree, toxic. Moreover, due to the chemical complexity in the synthesis process, some of the TE materials are not reproducible. Similarly, the scarcity of TE materials hampers their scalability. To address the above issues, this study presents an inexpensive, nontoxic, scalable, and highly reproducible paint-based TE module for the conversion of heat energy to electrical energy. Transport properties with structural analysis indicate that the electrical conductivity of the paint TE material is controlled by the concentration of graphite and sodium silicate, while the Seebeck coefficient is dominated by the ratio of n- and p-type Bi-Sb-Te. The results indicate that the as-developed TE module can withstand an operating temperature of up to 160 °C. At a temperature of 57 °C, the highest power factors of the as-synthesized n- and p-type TE paints are 1.34 and 1.42 μW/(cm K2), respectively. It is also found that the TE module can have a higher output voltage when the cold side of the TE module is allowed to float in the air in comparison to that when it is in contact with the human body. The performance of the paint-based TE module is measured on five parts of the body, namely, the chest, palm, leg, wrist, and neck; the wrist has the highest open-circuit voltage of 1.9 mV, indicating its suitability for wearable applications. Finally, at a temperature gradient of 30 °C, a maximum output power of 6.8 μW is attained.
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Affiliation(s)
- Muhammed Yilmaz
- Department of Chemical Engineering, Istanbul University-Cerrahpaşa, Avcılar 34320, Istanbul, Turkey
| | - Aminu Yusuf
- Department of Engineering Sciences, Istanbul University-Cerrahpaşa, Avcılar 34320, Istanbul, Turkey
| | - Koray Gurkan
- Department of Electrical and Electronics Engineering, Istanbul University-Cerrahpaşa, Avcılar 34320, Istanbul, Turkey
| | - Sedat Ballikaya
- Department of Engineering Sciences, Istanbul University-Cerrahpaşa, Avcılar 34320, Istanbul, Turkey
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Dervisevic M, Jara Fornerod MJ, Harberts J, Zangabad PS, Voelcker NH. Wearable Microneedle Patch for Transdermal Electrochemical Monitoring of Urea in Interstitial Fluid. ACS Sens 2024; 9:932-941. [PMID: 38252743 DOI: 10.1021/acssensors.3c02386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Microneedle-based wearable electrochemical biosensors are the new frontier in personalized health monitoring and disease diagnostic devices that provide an alternative tool to traditional blood-based invasive techniques. Advancements in micro- and nanofabrication technologies enabled the fabrication of microneedles using different biomaterials and morphological features with the aim of overcoming existing challenges and enhancing sensing performance. In this work, we report a microneedle array featuring conductive recessed microcavities for monitoring urea levels in the interstitial fluid of the skin. Microcavities are small pockets on the tip of each microneedle that can accommodate the sensing layer, provide protection from delamination during skin insertion or removal, and position the sensing layer in a deep layer of the skin to reach the interstitial fluid. The wearable urea patch has shown to be highly sensitive and selective in monitoring urea, with a sensitivity of 2.5 mV mM-1 and a linear range of 3 to 18 mM making it suitable for monitoring urea levels in healthy individuals and patients. Our ex vivo experiments have shown that recessed microcavities can protect the sensing layer from delamination during skin insertion and monitor changing urea levels in interstitial fluid. This biocompatible platform provides alternative solutions to the critical issue of maintaining the performance of the biosensor upon skin insertion and holds great potential for advancing transdermal sensor technology.
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Affiliation(s)
- Muamer Dervisevic
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
| | - Maximiliano Jesus Jara Fornerod
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
| | - Jann Harberts
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
| | - Parham Sahandi Zangabad
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
| | - Nicolas H Voelcker
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
- Materials Science and Engineering, Monash University, Clayton, Victoria 3168, Australia
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Agarwal AK, Gonzales R, Scott K, Merchant R. Investigating the Feasibility of Using a Wearable Device to Measure Physiologic Health Data in Emergency Nurses and Residents: Observational Cohort Study. JMIR Form Res 2024; 8:e51569. [PMID: 38386373 PMCID: PMC10921319 DOI: 10.2196/51569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/20/2023] [Accepted: 01/07/2024] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Emergency departments play a pivotal role in the US health care system, with high use rates and inherent stress placed on patients, patient care, and clinicians. The impact of the emergency department environment on the health and well-being of emergency residents and nurses can be seen in worsening rates of burnout and cardiovascular health. Research on clinician health has historically been completed outside of clinical areas and not personalized to the individual. The expansion of digital technology, specifically wearable devices, may enhance the ability to understand how health care environments impact clinicians. OBJECTIVE The primary objective of this pilot study was to assess the feasibility and acceptability of using wearable devices to measure and record physiologic data from emergency nurses and resident physicians. Understanding strategies that are accepted and used by clinicians is critical prior to launching larger investigations aimed at improving outcomes. METHODS This was a longitudinal pilot study conducted at an academic, urban, level 1 trauma center. A total of 20 participants, including emergency medicine resident physicians and nurses, were equipped with a wearable device (WHOOP band) and access to a mobile health platform for 6 weeks. Baseline surveys assessed burnout, mental health, and expectations of the device and experience. Participants provided open-ended feedback on the device and platform, contributing to the assessment of acceptance, adoption, and use of the wearable device. Secondary measures explored early signs and variations in heart rate variability, sleep, recovery, burnout, and mental health assessments. RESULTS Of the 20 participants, 10 consistently used the wearable device. Feedback highlighted varying experiences with the device, with a preference for more common wearables like the Apple Watch or Fitbit. Resident physicians demonstrated higher engagement with the device and platform as compared with nurses. Baseline mental health assessments indicated mild anxiety and depressive symptoms among participants. The Professional Fulfillment Index revealed low professional fulfillment, moderate workplace exhaustion, and interpersonal disengagement. CONCLUSIONS This pilot study underscores the potential of wearable devices in monitoring emergency clinicians' physiologic data but reveals challenges related to device preferences and engagement. The key takeaway is the necessity to optimize device and platform design for clinician use. Larger, randomized trials are recommended to further explore and refine strategies for leveraging wearable technology to support the well-being of the emergency workforce.
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Affiliation(s)
- Anish K Agarwal
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Center for Health Care Transformation and Innovation, Penn Medicine, Philadelphia, PA, United States
| | - Rachel Gonzales
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Center for Health Care Transformation and Innovation, Penn Medicine, Philadelphia, PA, United States
| | - Kevin Scott
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Raina Merchant
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Center for Health Care Transformation and Innovation, Penn Medicine, Philadelphia, PA, United States
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Tegegne TK, Tran LD, Nourse R, Gurrin C, Maddison R. Daily Activity Lifelogs of People With Heart Failure: Observational Study. JMIR Form Res 2024; 8:e51248. [PMID: 38381484 PMCID: PMC10918541 DOI: 10.2196/51248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/01/2023] [Accepted: 11/22/2023] [Indexed: 02/22/2024] Open
Abstract
BACKGROUND Globally, heart failure (HF) affects more than 64 million people, and attempts to reduce its social and economic burden are a public health priority. Interventions to support people with HF to self-manage have been shown to reduce hospitalizations, improve quality of life, and reduce mortality rates. Understanding how people self-manage is imperative to improve future interventions; however, most approaches to date, have used self-report methods to achieve this. Wearable cameras provide a unique tool to understand the lived experiences of people with HF and the daily activities they undertake, which could lead to more effective interventions. However, their potential for understanding chronic conditions such as HF is unclear. OBJECTIVE This study aimed to determine the potential utility of wearable cameras to better understand the activities of daily living in people living with HF. METHODS The "Seeing is Believing (SIB)" study involved 30 patients with HF who wore wearable cameras for a maximum of 30 days. We used the E-Myscéal web-based lifelog retrieval system to process and analyze the wearable camera image data set. Search terms for 7 daily activities (physical activity, gardening, shopping, screen time, drinking, eating, and medication intake) were developed and used for image retrieval. Sensitivity analysis was conducted to compare the number of images retrieved using different search terms. Temporal patterns in daily activities were examined, and differences before and after hospitalization were assessed. RESULTS E-Myscéal exhibited sensitivity to specific search terms, leading to significant variations in the number of images retrieved for each activity. The highest number of images returned were related to eating and drinking, with fewer images for physical activity, screen time, and taking medication. The majority of captured activities occurred before midday. Notably, temporal differences in daily activity patterns were observed for participants hospitalized during this study. The number of medication images increased after hospital discharge, while screen time images decreased. CONCLUSIONS Wearable cameras offer valuable insights into daily activities and self-management in people living with HF. E-Myscéal efficiently retrieves relevant images, but search term sensitivity underscores the need for careful selection.
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Ogata H, Negishi Y, Koizumi N, Nagayama H, Kaneko M, Kiyono K, Omi N. Individually optimized estimation of energy expenditure in rescue workers using a tri-axial accelerometer and heart rate monitor. Front Physiol 2024; 15:1322881. [PMID: 38434137 PMCID: PMC10905789 DOI: 10.3389/fphys.2024.1322881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/23/2024] [Indexed: 03/05/2024] Open
Abstract
Objectives: This study aimed to provide an improved energy expenditure estimation for heavy-load physical labor using accelerometer data and heart rate (HR) measured by wearables and to support food preparation and supply management for disaster relief and rescue operations as an expedition team. Methods: To achieve an individually optimized estimation for energy expenditure, a model equation parameter was determined based on the measurements of physical activity and HR during simulated rescue operations. The metabolic equivalent of task (MET), which was measured by using a tri-axial accelerometer and individual HR, was used, where two (minimum and maximum) or three (minimum, intermediate, and maximum) representative reference points were selected for each individual model fitting. In demonstrating the applicability of our approach in a realistic situation, accelerometer-based METs and HR of 30 males were measured using the tri-axial accelerometer and wearable HR during simulated rescue operations over 2 days. Results: Data sets of 27 rescue operations (age:34.2 ± 7.5 years; body mass index (BMI):22.9 ± 1.5 kg/m2) were used for the energy expenditure estimation after excluding three rescue workers due to their activity type and insufficient HR measurement. Using the combined approach with a tri-axial accelerometer and HR, the total energy expenditure increased by 143% for two points and 133% for three points, compared with the estimated total energy expenditure using only the accelerometer-based method. Conclusion: The use of wearables provided a reasonable estimation of energy expenditure for physical workers with heavy equipment. The application of our approach to disaster relief and rescue operations can provide important insights into nutrition and healthcare management.
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Affiliation(s)
- Hitomi Ogata
- Graduate School of Humanities and Social Sciences, Hiroshima University, Hiroshima, Japan
| | - Yutaro Negishi
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Nao Koizumi
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Hisashi Nagayama
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Miki Kaneko
- Graduate School of Engineering Science, Osaka University, Toyonaka, Japan
| | - Ken Kiyono
- Graduate School of Engineering Science, Osaka University, Toyonaka, Japan
| | - Naomi Omi
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
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Lyzwinski L, Elgendi M, Menon C. Innovative Approaches to Menstruation and Fertility Tracking Using Wearable Reproductive Health Technology: Systematic Review. J Med Internet Res 2024; 26:e45139. [PMID: 38358798 PMCID: PMC10905339 DOI: 10.2196/45139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 08/02/2023] [Accepted: 10/27/2023] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Emerging digital health technology has moved into the reproductive health market for female individuals. In the past, mobile health apps have been used to monitor the menstrual cycle using manual entry. New technological trends involve the use of wearable devices to track fertility by assessing physiological changes such as temperature, heart rate, and respiratory rate. OBJECTIVE The primary aims of this study are to review the types of wearables that have been developed and evaluated for menstrual cycle tracking and to examine whether they may detect changes in the menstrual cycle in female individuals. Another aim is to review whether these devices are effective for tracking various stages in the menstrual cycle including ovulation and menstruation. Finally, the secondary aim is to assess whether the studies have validated their findings by reporting accuracy and sensitivity. METHODS A review of PubMed or MEDLINE was undertaken to evaluate wearable devices for their effectiveness in predicting fertility and differentiating between the different stages of the menstrual cycle. RESULTS Fertility cycle-tracking wearables include devices that can be worn on the wrists, on the fingers, intravaginally, and inside the ear. Wearable devices hold promise for predicting different stages of the menstrual cycle including the fertile window and may be used by female individuals as part of their reproductive health. Most devices had high accuracy for detecting fertility and were able to differentiate between the luteal phase (early and late), fertile window, and menstruation by assessing changes in heart rate, heart rate variability, temperature, and respiratory rate. CONCLUSIONS More research is needed to evaluate consumer perspectives on reproductive technology for monitoring fertility, and ethical issues around the privacy of digital data need to be addressed. Additionally, there is also a need for more studies to validate and confirm this research, given its scarcity, especially in relation to changes in respiratory rate as a proxy for reproductive cycle staging.
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Affiliation(s)
- Lynnette Lyzwinski
- Menrva Research Group, School of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Vancouver, BC, Canada
| | - Mohamed Elgendi
- Biomedical and Mobile Health Technology Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Carlo Menon
- Menrva Research Group, School of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Vancouver, BC, Canada
- Biomedical and Mobile Health Technology Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
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Kohler I, Perrotta MV, Ferreira T, Eagleman DM. Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation. JMIRx Med 2024; 5:v5i1e49969. [PMID: 38345294 PMCID: PMC11008433 DOI: 10.2196/49969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 11/23/2023] [Accepted: 12/13/2023] [Indexed: 04/13/2024]
Abstract
Background High-frequency hearing loss is one of the most common problems in the aging population and with those who have a history of exposure to loud noises. This type of hearing loss can be frustrating and disabling, making it difficult to understand speech communication and interact effectively with the world. Objective This study aimed to examine the impact of spatially unique haptic vibrations representing high-frequency phonemes on the self-perceived ability to understand conversations in everyday situations. Methods To address high-frequency hearing loss, a multi-motor wristband was developed that uses machine learning to listen for specific high-frequency phonemes. The wristband vibrates in spatially unique locations to represent which phoneme was present in real time. A total of 16 participants with high-frequency hearing loss were recruited and asked to wear the wristband for 6 weeks. The degree of disability associated with hearing loss was measured weekly using the Abbreviated Profile of Hearing Aid Benefit (APHAB). Results By the end of the 6-week study, the average APHAB benefit score across all participants reached 12.39 points, from a baseline of 40.32 to a final score of 27.93 (SD 13.11; N=16; P=.002, 2-tailed dependent t test). Those without hearing aids showed a 10.78-point larger improvement in average APHAB benefit score at 6 weeks than those with hearing aids (t14=2.14; P=.10, 2-tailed independent t test). The average benefit score across all participants for ease of communication was 15.44 (SD 13.88; N=16; P<.001, 2-tailed dependent t test). The average benefit score across all participants for background noise was 10.88 (SD 17.54; N=16; P=.03, 2-tailed dependent t test). The average benefit score across all participants for reverberation was 10.84 (SD 16.95; N=16; P=.02, 2-tailed dependent t test). Conclusions These findings show that vibrotactile sensory substitution delivered by a wristband that produces spatially distinguishable vibrations in correspondence with high-frequency phonemes helps individuals with high-frequency hearing loss improve their perceived understanding of verbal communication. Vibrotactile feedback provides benefits whether or not a person wears hearing aids, albeit in slightly different ways. Finally, individuals with the greatest perceived difficulty understanding speech experienced the greatest amount of perceived benefit from vibrotactile feedback.
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Affiliation(s)
| | | | | | - David M Eagleman
- Neosensory, Los Altos, CA, United States
- Department of Psychiatry, Stanford University, Stanford, CA, United States
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Ahn CY, Lee JS. Digital Phenotyping for Real-Time Monitoring of Nonsuicidal Self-Injury: Protocol for a Prospective Observational Study. JMIR Res Protoc 2024; 13:e53597. [PMID: 38329791 PMCID: PMC10884894 DOI: 10.2196/53597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/29/2023] [Accepted: 01/18/2024] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND Nonsuicidal self-injury (NSSI) is a major global health concern. The limitations of traditional clinical and laboratory-based methodologies are recognized, and there is a pressing need to use novel approaches for the early detection and prevention of NSSI. Unfortunately, there is still a lack of basic knowledge of a descriptive nature on NSSI, including when, how, and why self-injury occurs in everyday life. Digital phenotyping offers the potential to predict and prevent NSSI by assessing objective and ecological measurements at multiple points in time. OBJECTIVE This study aims to identify real-time predictors and explain an individual's dynamic course of NSSI. METHODS This study will use a hybrid approach, combining elements of prospective observational research with non-face-to-face study methods. This study aims to recruit a cohort of 150 adults aged 20 to 29 years who have self-reported engaging in NSSI on 5 or more days within the past year. Participants will be enrolled in a longitudinal study conducted at 3-month intervals, spanning 3 long-term follow-up phases. The ecological momentary assessment (EMA) technique will be used via a smartphone app. Participants will be prompted to complete a self-injury and suicidality questionnaire and a mood appraisal questionnaire 3 times a day for a duration of 14 days. A wrist-worn wearable device will be used to collect heart rate, step count, and sleep patterns from participants. Dynamic structural equation modeling and machine learning approaches will be used. RESULTS Participant recruitment and data collection started in October 2023. Data collection and analysis are expected to be completed by December 2024. The results will be published in a peer-reviewed journal and presented at scientific conferences. CONCLUSIONS The insights gained from this study will not only shed light on the underlying mechanisms of NSSI but also pave the way for the development of tailored and culturally sensitive treatment options that can effectively address this major mental health concern. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/53597.
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Affiliation(s)
- Chan-Young Ahn
- Department of Psychology, Kangwon National University, Chuncheon-si, Republic of Korea
| | - Jong-Sun Lee
- Department of Psychology, Kangwon National University, Chuncheon-si, Republic of Korea
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Herrin KR, Kwak ST, Rock CG, Chang YH. Gait quality in prosthesis users is reflected by force-based metrics when learning to walk on a new research-grade powered prosthesis. Front Rehabil Sci 2024; 5:1339856. [PMID: 38370855 PMCID: PMC10869520 DOI: 10.3389/fresc.2024.1339856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 01/12/2024] [Indexed: 02/20/2024]
Abstract
Introduction Powered prosthetic feet require customized tuning to ensure comfort and long-term success for the user, but tuning in both clinical and research settings is subjective, time intensive, and the standard for tuning can vary depending on the patient's and the prosthetist's experience levels. Methods Therefore, we studied eight different metrics of gait quality associated with use of a research-grade powered prosthetic foot in seven individuals with transtibial amputation during treadmill walking. We compared clinically tuned and untuned conditions with the goal of identifying performance-based metrics capable of distinguishing between good (as determined by a clinician) from poor gait quality. Results Differences between the tuned and untuned conditions were reflected in ankle power, both the vertical and anterior-posterior impulse symmetry indices, limb-force alignment, and positive ankle work, with improvements seen in all metrics during use of the tuned prosthesis. Discussion Notably, all of these metrics relate to the timing of force generation during walking which is information not directly accessible to a prosthetist during a typical tuning process. This work indicates that relevant, real-time biomechanical data provided to the prosthetist through the future provision of wearable sensors may enhance and improve future clinical tuning procedures associated with powered prostheses as well as their long-term outcomes.
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Affiliation(s)
- Kinsey R. Herrin
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States
- Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, United States
| | - Samuel T. Kwak
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, United States
| | - Chase G. Rock
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, United States
| | - Young-Hui Chang
- Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, United States
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, United States
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Olejua P, McLain AC, Inak N, Dowda M, Pate RR. Clustering Patterns of 24-Hour Physical Activity in Children 6-36 Months Old. Pediatr Exerc Sci 2024:1-8. [PMID: 38307017 DOI: 10.1123/pes.2023-0055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 11/15/2023] [Accepted: 11/27/2023] [Indexed: 02/04/2024]
Abstract
PURPOSE To determine 24-hour physical activity (PA) clusters in children 6-36 months of age, factors associated with the clusters, and their agreement across time. METHOD A longitudinal study followed 150 infants from South Carolina up to 36 months of age. Measures included 24-hour PA and demographic data. Functional clustering was used to obtain the clusters. The association between cluster membership and infant/parent characteristics was examined by Kruskal-Wallis and chi-squared tests. Concordance was measured with the kappa coefficient and percent agreement. RESULTS At each follow-up, 3 clusters were optimal, identified as late activity (cluster 1), high activity (cluster 2), and medium activity (cluster 3). The defining feature of the late activity cluster was that their physical activity (PA) activity was shifted to later in the day versus children in clusters 2 and 3. At 6 months, the clusters were associated with race (<0.001), crawling (0.043), other children in the household (0.043), and mother's education (0.004); at 12 months with race (0.029), childcare (<0.001), and education (<0.001); and at 36 months with other children in the household (0.019). Clusters showed moderate agreement (kappa = .41 [.25 to .57], agreement = 61% [49% to 72%]) between 6 and 12 months and, at 36 months, showed no agreement with either 6 or 12 months. CONCLUSION Twenty-four-hour PA can be clustered into medium, high, and late PA. Further research is needed into the consequences of late sleeping in children at this age. Clusters are associated with household and childcare factors, and cluster membership is dynamic across time.
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Affiliation(s)
- Peter Olejua
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC,USA
| | - Alexander C McLain
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC,USA
| | - Nabila Inak
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC,USA
| | - Marsha Dowda
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC,USA
| | - Russell R Pate
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC,USA
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Robinson SA, Shimada SL, Zocchi MS, Etingen B, Smith B, McMahon N, Cutrona SL, Harmon JS, Wilck NR, Hogan TP. Factors Associated with Veteran Self-Reported Use of Digital Health Devices. J Gen Intern Med 2024; 39:79-86. [PMID: 38252248 PMCID: PMC10937849 DOI: 10.1007/s11606-023-08479-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/12/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND Digital health devices (DHDs), technologies designed to gather, monitor, and sometimes share data about health-related behaviors or symptoms, can support the prevention or management of chronic conditions. DHDs range in complexity and utility, from tracking lifestyle behaviors (e.g., pedometer) to more sophisticated biometric data collection for disease self-management (e.g., glucometers). Despite these positive health benefits, supporting adoption and sustained use of DHDs remains a challenge. OBJECTIVE This analysis examined the prevalence of, and factors associated with, DHD use within the Veterans Health Administration (VHA). DESIGN National survey. PARTICIPANTS Veterans who receive VHA care and are active secure messaging users. MAIN MEASURES Demographics, access to technology, perceptions of using health technologies, and use of lifestyle monitoring and self-management DHDs. RESULTS Among respondents, 87% were current or past users of at least one DHD, and 58% were provided a DHD by VHA. Respondents 65 + years were less likely to use a lifestyle monitoring device (AOR 0.57, 95% CI [0.39, 0.81], P = .002), but more likely to use a self-management device (AOR 1.69, 95% [1.10, 2.59], P = .016). Smartphone owners were more likely to use a lifestyle monitoring device (AOR 2.60, 95% CI [1.42, 4.75], P = .002) and a self-management device (AOR 1.83, 95% CI [1.04, 3.23], P = .037). CONCLUSIONS The current analysis describes the types of DHDs that are being adopted by Veterans and factors associated with their adoption. Results suggest that various factors influence adoption, including age, access to technology, and health status, and that these relationships may differ based on the functionalities of the device. VHA provision of devices was frequent among device users. Providing Veterans with DHDs and the training needed to use them may be important factors in facilitating device adoption. Taken together, this knowledge can inform future implementation efforts, and next steps to support patient-team decision making about DHD use.
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Affiliation(s)
- Stephanie A Robinson
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA.
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA.
- The Pulmonary Center, Boston University School of Medicine, Boston, MA, USA.
| | - Stephanie L Shimada
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Department of Health Law, Policy, & Management, Boston University School of Public Health, Boston, MA, USA
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Mark S Zocchi
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA
| | - Bella Etingen
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center of Innovation for Complex Chronic Healthcare, Hines Veterans Affairs Hospital, Hines, IL, USA
| | - Bridget Smith
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center of Innovation for Complex Chronic Healthcare, Hines Veterans Affairs Hospital, Hines, IL, USA
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Nicholas McMahon
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
| | - Sarah L Cutrona
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Julie S Harmon
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Office of Connected Care, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC, USA
| | - Nancy R Wilck
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Office of Connected Care, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC, USA
| | - Timothy P Hogan
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, 200 Springs Rd., Bldg. 70 Room 263, Bedford, MA, 01730, USA
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Peter O'Donnell Jr School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Sholokhova K, Jian WS, Yang HC, Li YCJ. Adjustable Cuffless Smartphone Attachment (ACSA+) for Estimation of Blood Pressure Trends: A Pilot Study. Stud Health Technol Inform 2024; 310:534-538. [PMID: 38269866 DOI: 10.3233/shti231022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Among the elderly, hypertension remains one of the prevalent health conditions, which requires monitoring and intervention strategies. Nevertheless, regular reporting of blood pressure (BP) from these individuals still poses multiple challenges. However, most people own cell phone and are engaged in phone conversations daily. Here, we propose an adjustable cuffless smartphone attachment (ACSA+) equipped with a PPG sensor for the estimation of BP during phone conversations. ACSA+ can be easily attached to the back of any modern cell phone. ACSA+ will help to continuously collect BP data and store it as a trend line.
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Affiliation(s)
- Kseniia Sholokhova
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Wen-Shan Jian
- Graduate Institute of Data Science, Taipei Medical University, Taipei, Taiwan
| | - Hsuan-Chia Yang
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Yu-Chuan Jack Li
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
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Azadi B, Haslgrübler M, Anzengruber-Tanase B, Sopidis G, Ferscha A. Robust Feature Representation Using Multi-Task Learning for Human Activity Recognition. Sensors (Basel) 2024; 24:681. [PMID: 38276371 PMCID: PMC10819053 DOI: 10.3390/s24020681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/11/2024] [Accepted: 01/19/2024] [Indexed: 01/27/2024]
Abstract
Learning underlying patterns from sensory data is crucial in the Human Activity Recognition (HAR) task to avoid poor generalization when coping with unseen data. A key solution to such an issue is representation learning, which becomes essential when input signals contain activities with similar patterns or when patterns generated by different subjects for the same activity vary. To address these issues, we seek a solution to increase generalization by learning the underlying factors of each sensor signal. We develop a novel multi-channel asymmetric auto-encoder to recreate input signals precisely and extract indicative unsupervised futures. Further, we investigate the role of various activation functions in signal reconstruction to ensure the model preserves the patterns of each activity in the output. Our main contribution is that we propose a multi-task learning model to enhance representation learning through shared layers between signal reconstruction and the HAR task to improve the robustness of the model in coping with users not included in the training phase. The proposed model learns shared features between different tasks that are indeed the underlying factors of each input signal. We validate our multi-task learning model using several publicly available HAR datasets, UCI-HAR, MHealth, PAMAP2, and USC-HAD, and an in-house alpine skiing dataset collected in the wild, where our model achieved 99%, 99%, 95%, 88%, and 92% accuracy. Our proposed method shows consistent performance and good generalization on all the datasets compared to the state of the art.
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Affiliation(s)
- Behrooz Azadi
- Pro2Future GmbH, Altenberger Strasse 69, 4040 Linz, Austria; (M.H.); (B.A.-T.); (G.S.)
| | - Michael Haslgrübler
- Pro2Future GmbH, Altenberger Strasse 69, 4040 Linz, Austria; (M.H.); (B.A.-T.); (G.S.)
| | | | - Georgios Sopidis
- Pro2Future GmbH, Altenberger Strasse 69, 4040 Linz, Austria; (M.H.); (B.A.-T.); (G.S.)
| | - Alois Ferscha
- Institute of Pervasive Computing, Johannes Kepler University, Altenberger Straße 69, 4040 Linz, Austria;
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García-Luna MA, Jimenez-Olmedo JM, Pueo B, Manchado C, Cortell-Tormo JM. Concurrent Validity of the Ergotex Device for Measuring Low Back Posture. Bioengineering (Basel) 2024; 11:98. [PMID: 38275578 PMCID: PMC10812927 DOI: 10.3390/bioengineering11010098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/17/2024] [Accepted: 01/18/2024] [Indexed: 01/27/2024] Open
Abstract
Highlighting the crucial role of monitoring and quantifying lumbopelvic rhythm for spinal curvature, the Ergotex IMU, a portable, lightweight, cost-effective, and energy-efficient technology, has been specifically designed for the pelvic and lumbar area. This study investigates the concurrent validity of the Ergotex device in measuring sagittal pelvic tilt angle. We utilized an observational, repeated measures design with healthy adult males (mean age: 39.3 ± 7.6 y, body mass: 82.2 ± 13.0 kg, body height: 179 ± 8 cm), comparing Ergotex with a 3D optical tracking system. Participants performed pelvic tilt movements in anterior, neutral, and posterior conditions. Statistical analysis included paired samples t-tests, Bland-Altman plots, and regression analysis. The findings show minimal systematic error (0.08° overall) and high agreement between the Ergotex and optical tracking, with most data points falling within limits of agreement of Bland-Altman plots (around ±2°). Significant differences were observed only in the anterior condition (0.35°, p < 0.05), with trivial effect sizes (ES = 0.08), indicating that these differences may not be clinically meaningful. The high Pearson's correlation coefficients across conditions underscore a robust linear relationship between devices (r > 0.9 for all conditions). Regression analysis showed a standard error of estimate (SEE) of 1.1° with small effect (standardized SEE < 0.26 for all conditions), meaning that the expected average deviation from the true value is around 1°. These findings validate the Ergotex as an effective, portable, and cost-efficient tool for assessing sagittal pelvic tilt, with practical implications in clinical and sports settings where traditional methods might be impractical or costly.
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Affiliation(s)
- Marco A. García-Luna
- Health, Physical Activity, and Sports Technology Research Group, Faculty of Education, University of Alicante, 03690 San Vicente del Raspeig, Spain; (M.A.G.-L.); (B.P.), (J.M.C.-T.)
| | - Jose M. Jimenez-Olmedo
- Health, Physical Activity, and Sports Technology Research Group, Faculty of Education, University of Alicante, 03690 San Vicente del Raspeig, Spain; (M.A.G.-L.); (B.P.), (J.M.C.-T.)
| | - Basilio Pueo
- Health, Physical Activity, and Sports Technology Research Group, Faculty of Education, University of Alicante, 03690 San Vicente del Raspeig, Spain; (M.A.G.-L.); (B.P.), (J.M.C.-T.)
| | - Carmen Manchado
- Sports Coaching and Performance Research Group, Faculty of Education, University of Alicante, 03690 San Vicente del Raspeig, Spain;
| | - Juan M. Cortell-Tormo
- Health, Physical Activity, and Sports Technology Research Group, Faculty of Education, University of Alicante, 03690 San Vicente del Raspeig, Spain; (M.A.G.-L.); (B.P.), (J.M.C.-T.)
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Sanchez Gomez J, Pramono RXA, Imtiaz SA, Rodriguez-Villegas E, Valido Morales A. Validation of a Wearable Medical Device for Automatic Diagnosis of OSA against Standard PSG. J Clin Med 2024; 13:571. [PMID: 38276077 PMCID: PMC10816319 DOI: 10.3390/jcm13020571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/16/2024] [Accepted: 01/17/2024] [Indexed: 01/27/2024] Open
Abstract
STUDY OBJECTIVE The objective of this study was to assess the accuracy of automatic diagnosis of obstructive sleep apnea (OSA) with a new, small, acoustic-based, wearable technology (AcuPebble SA100), by comparing it with standard type 1 polysomnography (PSG) diagnosis. MATERIAL AND METHODS This observational, prospective study was carried out in a Spanish hospital sleep apnea center. Consecutive subjects who had been referred to the hospital following primary care suspicion of OSA were recruited and underwent in-laboratory attended PSG, together with the AcuPebble SA100 device simultaneously overnight from January to December 2022. RESULTS A total of 80 patients were recruited for the trial. The patients had a median Epworth scoring of 10, a mean of 10.4, and a range of 0-24. The mean AHI obtained with PSG plus sleep clinician marking was 23.2, median 14.3 and range 0-108. The study demonstrated a diagnostic accuracy (based on AHI) of 95.24%, sensitivity of 92.86%, specificity of 97.14%, positive predictive value of 96.30%, negative predictive value of 94.44%, positive likelihood ratio of 32.50 and negative likelihood ratio of 0.07. CONCLUSIONS The AcuPebble SA100 (EU) device has demonstrated an accurate automated diagnosis of OSA in patients undergoing in-clinic sleep testing when compared against the gold-standard reference of in-clinic PSG.
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Affiliation(s)
- Jesus Sanchez Gomez
- Sleep Unit, Pneumology Department, Virgen Macarena University Hospital, 41009 Seville, Spain; (J.S.G.); (A.V.M.)
| | | | - Syed Anas Imtiaz
- Wearable Technologies Lab, EEE Department, Imperial College London, London SW7 2AZ, UK; (S.A.I.); (E.R.-V.)
| | - Esther Rodriguez-Villegas
- Wearable Technologies Lab, EEE Department, Imperial College London, London SW7 2AZ, UK; (S.A.I.); (E.R.-V.)
| | - Agustin Valido Morales
- Sleep Unit, Pneumology Department, Virgen Macarena University Hospital, 41009 Seville, Spain; (J.S.G.); (A.V.M.)
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Kuwajima Y, Yamaguchi Y, Yamada Y, Morita T, Wiranata A, Minaminosono A, Hosoya N, Kakehi Y, Maeda S. Pocketable and Smart Electrohydrodynamic Pump for Clothes. ACS Appl Mater Interfaces 2024; 16:1883-1891. [PMID: 38096263 PMCID: PMC10788827 DOI: 10.1021/acsami.3c15274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 01/12/2024]
Abstract
Seamlessly fusing fashion and functionality can redefine wearable technology and enhance the quality of life. We propose a pocketable and smart electrohydrodynamic pump (PSEP) with self-sensing capability for wearable thermal controls. Overcoming the constraints of traditional liquid-cooled wearables, PSEP with dimensions of 10 × 2 × 1.05 cm and a weight of 10 g is sufficiently compact to fit into a shirt pocket, providing stylish and unobtrusive thermal control. Silent operation coupled with the unique self-sensing ability to monitor the flow rate ensures system reliability without cumbersome additional components. The significant contribution of our study is the formulation and validation of a theoretical model for self-sensing in EHD pumps, thereby introducing an innovative functionality to EHD pump technology. PSEP can deliver temperature changes of up to 3 °C, considerably improving personal comfort. Additionally, the PSEP system features an intuitive, smartphone-compatible interface for seamless wireless control and monitoring, enhancing user interaction and convenience. Furthermore, the ability to detect and notify users of flow blockages, achieved by self-sensing, ensures an efficient and long-term operation. Through its blend of compact design, intelligent functionality, and stylish integration into daily wear, PSEP reshapes the landscape of wearable thermal control technology and offers a promising avenue for enhancing personal comfort in daily life.
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Affiliation(s)
- Yu Kuwajima
- Department
of Engineering Science and Mechanics, Shibaura
Institute of Technology, 3-7-5, Toyosu, Koto-ku, Tokyo 135-8548, Japan
| | - Yuya Yamaguchi
- Department
of Engineering Science and Mechanics, Shibaura
Institute of Technology, 3-7-5, Toyosu, Koto-ku, Tokyo 135-8548, Japan
| | - Yuhei Yamada
- Living
Systems Materialogy Research Group, International Research Frontiers
Initiative, Tokyo Institute of Technology, 4259, Nagatsuta-Cho, Midori-Ku, Yokohama, Kanagawa 226-8501, Japan
| | - Takafumi Morita
- The
University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
| | - Ardi Wiranata
- Department
of Mechanical and Industrial Engineering, Universitas Gadjah Mada, Jalan Grafika No. 2, Yogyakarta 55281, Indonesia
| | - Ayato Minaminosono
- Department
of Engineering Science and Mechanics, Shibaura
Institute of Technology, 3-7-5, Toyosu, Koto-ku, Tokyo 135-8548, Japan
| | - Naoki Hosoya
- Department
of Engineering Science and Mechanics, Shibaura
Institute of Technology, 3-7-5, Toyosu, Koto-ku, Tokyo 135-8548, Japan
| | - Yasuaki Kakehi
- The
University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
| | - Shingo Maeda
- Department
of Mechanical Engineering, Tokyo Institute
of Technology, Ookayama, Meguro-ku, Tokyo 152-8550, Japan
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Tucker S, Jonnalagadda S, Beseler C, Yoder A, Fruhling A. Exploring wearable technology use and importance of health monitoring in the hazardous occupations of first responders and professional drivers. J Occup Health 2024; 66:uiad002. [PMID: 38332724 PMCID: PMC11020306 DOI: 10.1093/joccuh/uiad002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 02/10/2024] Open
Abstract
OBJECTIVES Hazardous materials (HAZMAT) pose risks to the health and safety of professionals involved with transportation and emergency responses. Two distinct occupational groups that encounter HAZMAT events are first responders and professional drivers. Wearable technology is a tool that can assist with monitoring the health of professionals involved in HAZMAT events. The aim of this study was to compare and evaluate the perceptions of first responders and professional drivers on wearable technology and attitudes toward health monitoring. METHODS A survey was administered to first responders (n = 112) and professional drivers (n = 218). Statistical approaches included bivariate analysis, latent class analysis, logistic regression analysis, and path analysis for the variables of interest. RESULTS There were significant differences between the groups in perceptions of the benefits of monitoring certain health indicators. Professional drivers were more likely to have a history of wearable technology use compared with first responders (odds ratio [OR] = 10.1; 95% CI, 4.42-22.9), reported greater exposure to HAZMAT (OR = 4.32; 95% CI, 2.24-8.32), and were more willing to have their health data monitored by someone other than themselves (OR = 9.27; 95% CI, 3.67-23.4). A multinomial regression model revealed that occupation was not a significant predictor of class preference for acceptance of monitoring specific health indicators. CONCLUSIONS Occupation appeared to be important but further analysis uncovered that characteristics of individuals within the occupations were more salient to the use of wearable technology. HAZMAT exposure, someone else monitoring health data, and experience with wearable technology use were found to be important factors for perceptions about benefits of health monitoring with wearable technology.
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Affiliation(s)
- Sarah Tucker
- Department of Environmental, Agricultural and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE, 68198, United States
| | - Soundarya Jonnalagadda
- Information Systems and Quantitative Analysis, College of Information Science & Technology, University of Nebraska, Omaha, NE, 68182, United States
| | - Cheryl Beseler
- Department of Environmental, Agricultural and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE, 68198, United States
| | - Aaron Yoder
- Department of Environmental, Agricultural and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE, 68198, United States
| | - Ann Fruhling
- School of Interdisciplinary Informatics, College of Information Science & Technology, University of Nebraska, Omaha, NE, 68182, United States
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García-Luna MA, Ruiz-Fernández D, Tortosa-Martínez J, Manchado C, García-Jaén M, Cortell-Tormo JM. Transparency as a Means to Analyse the Impact of Inertial Sensors on Users during the Occupational Ergonomic Assessment: A Systematic Review. Sensors (Basel) 2024; 24:298. [PMID: 38203160 PMCID: PMC10781389 DOI: 10.3390/s24010298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/19/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
The literature has yielded promising data over the past decade regarding the use of inertial sensors for the analysis of occupational ergonomics. However, despite their significant advantages (e.g., portability, lightness, low cost, etc.), their widespread implementation in the actual workplace has not yet been realized, possibly due to their discomfort or potential alteration of the worker's behaviour. This systematic review has two main objectives: (i) to synthesize and evaluate studies that have employed inertial sensors in ergonomic analysis based on the RULA method; and (ii) to propose an evaluation system for the transparency of this technology to the user as a potential factor that could influence the behaviour and/or movements of the worker. A search was conducted on the Web of Science and Scopus databases. The studies were summarized and categorized based on the type of industry, objective, type and number of sensors used, body parts analysed, combination (or not) with other technologies, real or controlled environment, and transparency. A total of 17 studies were included in this review. The Xsens MVN system was the most widely used in this review, and the majority of studies were classified with a moderate level of transparency. It is noteworthy, however, that there is a limited and worrisome number of studies conducted in uncontrolled real environments.
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Affiliation(s)
- Marco A. García-Luna
- Department of General and Specific Didactics, Faculty of Education, University of Alicante, 03690 Alicante, Spain; (J.T.-M.); (C.M.); (M.G.-J.); (J.M.C.-T.)
| | - Daniel Ruiz-Fernández
- Department of Computer Science and Technology, University of Alicante, 03690 Alicante, Spain;
| | - Juan Tortosa-Martínez
- Department of General and Specific Didactics, Faculty of Education, University of Alicante, 03690 Alicante, Spain; (J.T.-M.); (C.M.); (M.G.-J.); (J.M.C.-T.)
| | - Carmen Manchado
- Department of General and Specific Didactics, Faculty of Education, University of Alicante, 03690 Alicante, Spain; (J.T.-M.); (C.M.); (M.G.-J.); (J.M.C.-T.)
| | - Miguel García-Jaén
- Department of General and Specific Didactics, Faculty of Education, University of Alicante, 03690 Alicante, Spain; (J.T.-M.); (C.M.); (M.G.-J.); (J.M.C.-T.)
| | - Juan M. Cortell-Tormo
- Department of General and Specific Didactics, Faculty of Education, University of Alicante, 03690 Alicante, Spain; (J.T.-M.); (C.M.); (M.G.-J.); (J.M.C.-T.)
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