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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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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 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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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 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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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. [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [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, The University of Texas at Austin, Austin, Texas, 78712-1139, UNITED STATES
| | - Zane Johnson
- McKetta Department of Chemical Engineering, The University of Texas at Austin, The University of Texas at Austin, Austin, Texas, 78712-1139, UNITED STATES
| | - Spencer Denton
- Chandra Family Department of Electrical Engineering, The University of Texas at Austin, The University of Texas at Austin, Austin, Texas, 78712-1139, UNITED STATES
| | - Ning Liu
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, The University of Texas at Austin, Austin, Texas, 78712-1139, UNITED STATES
| | - Deji Akinwande
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, The University of Texas at Austin, Austin, Texas, 78712-1139, UNITED STATES
| | - Emily Porter
- Biomedical Engineering, McGill University, McGill University, Montreal, Quebec, H3A 0G4, CANADA
| | - Dmitry Kireev
- Biomedical Engineering, University of Massachusetts Amherst, University of Massachusetts Amherst, Amherst, Massachusetts, 01003, UNITED STATES
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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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6
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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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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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9
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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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10
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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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12
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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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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. [PMID: 38497429 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] [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 Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Chenlu Gao
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Lei Gao
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Ruixue Cai
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Kun Hu
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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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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16
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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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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. [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] [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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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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32
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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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Van Hooren B, Willems P, Plasqui G, Meijer K. Changes in running economy and running technique following 6 months of running with and without wearable-based real-time feedback. Scand J Med Sci Sports 2024; 34:e14565. [PMID: 38268070 DOI: 10.1111/sms.14565] [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: 07/03/2023] [Revised: 11/23/2023] [Accepted: 01/07/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND An increasing number of commercially available wearables provide real-time feedback on running biomechanics with the aim to reduce injury risk or improve performance. OBJECTIVE Investigate whether real-time feedback by wearable insoles (ARION) alters running biomechanics and improves running economy more as compared to unsupervised running training. We also explored the correlation between changes in running biomechanics and running economy. METHODS Forty recreational runners were randomized to an intervention and control group and performed ~6 months of in-field training with or without wearable-based real-time feedback on running technique and speed. Running economy and running biomechanics were measured in lab conditions without feedback pre and post intervention at four speeds. RESULTS Twenty-two individuals (13 control, 9 intervention) completed both tests. Both groups significantly reduced their energetic cost by an average of -6.1% and -7.7% for the control and intervention groups, respectively. The reduction in energy cost did not significantly differ between groups overall (-0.07 ± 0.14 J∙kg∙m-1 , -1.5%, p = 0.63). There were significant changes in spatiotemporal metrics, but their magnitude was minor and did not differ between the groups. There were no significant changes in running kinematics within or between groups. However, alterations in running biomechanics beyond typical session-to-session variation were observed during some in-field sessions for individuals that received real-time feedback. CONCLUSION Alterations in running biomechanics as observed during some in-field sessions for individuals receiving wearable-based real-time feedback did not result in significant differences in running economy or running biomechanics when measured in controlled lab conditions without feedback.
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Affiliation(s)
- Bas Van Hooren
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands
| | - Paul Willems
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands
| | - Guy Plasqui
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands
| | - Kenneth Meijer
- Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands
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Thyla B, Bai VT. A very low-profile CPW based conformal antenna for wearable/implantable applications. Technol Health Care 2024; 32:103-115. [PMID: 37545263 DOI: 10.3233/thc-220534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
BACKGROUND In wireless communication standard 4G and 5G, the body centric network plays an important role for the wireless communication between various devices. OBJECTIVE This research relates to a wide-band conformal co-planar waveguide (CPW) antenna for wearable applications. METHODS The proposed CPW antenna is printed on 0.1 mm thick bio-compatible polymide substrate whose dielectric constant and permittivity are 3.5 and 0.02 respectively. The total area of the antenna is around 17.5 × 15 mm2 which is significantly smaller than the wearable antennas proposed in literature. The proposed antenna is designed to operate in new ISM band 5.8 GHz with the bandwidth of 5.3-6.3 GHz with 2:1 Voltage Standing Wave Ratio (VSWR). The antenna is printed on the flexible substrate and hence robustness of device is evaluated by bending analysis. It reveals the superior performance of the designed CPW antenna over the desired spectrum of operation. RESULTS Specific Absorption Rate (SAR) is calculated after placing the antenna at various places of human phantom model and showed that SAR values are below 1.6 W/Kg which is the maximum margin recommended by Federal Communication Commission (FCC), i.e when tested with 1 g and 10 g of human tissue of phantom model, for the test frequency range of 5.5-6.1 GHz, SAR value falls between 0.9987 and 0.921 W/Kg respectively. The antenna also shows the radiation efficiency around 92% with overall realized gain 5.2 dBi which are substantial values for wearable applications. CONCLUSION The outcomes of this research revealed the feasibility of the recommended antenna becoming a major contender of future Internet of Things (IoT) applications.
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Vandenbussche N, Van Der Donckt J, De Brouwer M, Steenwinckel B, Stojchevska M, Ongenae F, Van Hoecke S, Paemeleire K. Patients with chronic cluster headache may show reduced activity energy expenditure on ambulatory wrist actigraphy recordings during daytime attacks. Brain Behav 2024; 14:e3360. [PMID: 38376015 PMCID: PMC10761329 DOI: 10.1002/brb3.3360] [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: 08/18/2023] [Revised: 11/23/2023] [Accepted: 11/25/2023] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVE To investigate the changes in activity energy expenditure (AEE) throughout daytime cluster headache (CH) attacks in patients with chronic CH and to evaluate the usefulness of actigraphy as a digital biomarker of CH attacks. BACKGROUND CH is a primary headache disorder characterized by attacks of severe to very severe unilateral pain (orbital, supraorbital, temporal, or in any combination of these sites), with ipsilateral cranial autonomic symptoms and/or a sense of restlessness or agitation. We hypothesized increased AEE from hyperactivity during attacks measured by actigraphy. METHODS An observational study including patients with chronic CH was conducted. During 21 days, patients wore an actigraphy device on the nondominant wrist and recorded CH attack-related data in a dedicated smartphone application. Accelerometer data were used for the calculation of AEE before and during daytime CH attacks that occurred in ambulatory settings, and without restrictions on acute and preventive headache treatment. We compared the activity and movements during the pre-ictal, ictal, and postictal phases with data from wrist-worn actigraphy with time-concordant intervals during non-headache periods. RESULTS Four patients provided 34 attacks, of which 15 attacks met the eligibility criteria for further analysis. In contrast with the initial hypothesis of increased energy expenditure during CH attacks, a decrease in movement was observed during the pre-ictal phase (30 min before onset to onset) and during the headache phase. A significant decrease (p < .01) in the proportion of high-intensity movement during headache attacks, of which the majority were oxygen-treated, was observed. This trend was less present for low-intensity movements. CONCLUSION The unexpected decrease in AEE during the pre-ictal and headache phase of daytime CH attacks in patients with chronic CH under acute and preventive treatment in ambulatory settings has important implications for future research on wrist actigraphy in CH.
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Affiliation(s)
- Nicolas Vandenbussche
- Department of NeurologyGhent University HospitalGhentBelgium
- Department of Basic and Applied Medical Sciences, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
| | | | | | | | | | | | | | - Koen Paemeleire
- Department of NeurologyGhent University HospitalGhentBelgium
- Department of Basic and Applied Medical Sciences, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
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Tas B, Walker H, Lawn W, Matcham F, Traykova EV, Evans RAS, Strang J. What impacts the acceptability of wearable devices that detect opioid overdose in people who use opioids? A qualitative study. Drug Alcohol Rev 2024; 43:213-225. [PMID: 37596977 DOI: 10.1111/dar.13737] [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: 03/07/2023] [Revised: 07/26/2023] [Accepted: 07/29/2023] [Indexed: 08/21/2023]
Abstract
INTRODUCTION Drug-related deaths involving an opioid are at all-time highs across the United Kingdom. Current overdose antidotes (naloxone) require events to be witnessed and recognised for reversal. Wearable technologies have potential for remote overdose detection or response but their acceptability among people who use opioids (PWUO) is not well understood. This study explored facilitators and barriers to wearable technology acceptability to PWUO. METHODS Twenty-four participants (79% male, average age 46 years) with current (n = 15) and past (n = 9) illicit heroin use and 54% (n = 13) who were engaged in opioid substitution therapy participated in semi-structured interviews (n = 7) and three focus groups (n = 17) in London and Nottingham from March to June 2022. Participants evaluated real devices, discussing characteristics, engagement factors, target populations, implementation strategies and preferences. Conversations were recorded, transcribed and thematically analysed. RESULTS Three themes emerged: device-, person- and environment-specific factors impacting acceptability. Facilitators included inconspicuousness under the device theme and targeting subpopulations of PWUO at the individual theme. Barriers included affordability of devices and limited technology access within the environment theme. Trust in device accuracy for high and overdose differentiation was a crucial facilitator, while trust between technology and PWUO was a significant environmental barrier. DISCUSSION AND CONCLUSIONS Determinants of acceptability can be categorised into device, person and environmental factors. PWUO, on the whole, require devices that are inconspicuous, comfortable, accessible, easy to use, controlled by trustworthy organisations and highly accurate. Device developers must consider how the type of end-user and their environment moderate acceptability of the device.
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Affiliation(s)
- Basak Tas
- National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hollie Walker
- National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Will Lawn
- National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Clinical Psychopharmacology Unit, University College London, London, UK
| | - Faith Matcham
- School of Psychology, University of Sussex, Falmer, UK
| | - Elena V Traykova
- National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Rebecca A S Evans
- National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - John Strang
- National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, Denmark Hill, London, UK
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Golparvar A, Thenot L, Boukhayma A, Carrara S. Soft Epidermal Paperfluidics for Sweat Analysis by Ratiometric Raman Spectroscopy. Biosensors (Basel) 2023; 14:12. [PMID: 38248389 PMCID: PMC10812966 DOI: 10.3390/bios14010012] [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: 11/21/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 01/23/2024]
Abstract
The expanding interest in digital biomarker analysis focused on non-invasive human bodily fluids, such as sweat, highlights the pressing need for easily manufactured and highly efficient soft lab-on-skin solutions. Here, we report, for the first time, the integration of microfluidic paper-based devices (μPAD) and non-enhanced Raman-scattering-enabled optical biochemical sensing (Raman biosensing). Their integration merges the enormous benefits of μPAD, with high potential for commercialization and use in resource-limited settings, with biorecognition-element-free (but highly selective) optical Raman biosensing. The introduced thin (0.36 mm), ultra-lightweight (0.19 g), and compact footprint (3 cm2) opto-paperfluidic sweat patch is flexible, stretchable, and conforms, irritation-free, to hairless or minimally haired body regions to enable swift sweat collection. As a great advantage, this new bio-chemical sensory system excels through its absence of onboard biorecognition elements (bioreceptor-free) and omission of plasmonic nanomaterials. The proposed easy fabrication process is adaptable to mass production by following a fully sustainable and cost-effective process utilizing only basic tools by avoiding typically employed printing or laser patterning. Furthermore, efficient collection and transportation of precise sweat volumes, driven exclusively by the wicking properties of porous materials, shows high efficiency in liquid transportation and reduces biosensing latency by a factor of 5 compared to state-of-the-art epidermal microfluidics. The proposed unit enables electronic chip-free and imaging-less visual sweat loss quantification as well as optical biochemical analysis when coupled with Raman spectroscopy. We investigated the multimodal quantification of sweat urea and lactate levels ex vivo (with syntactic sweat including +30 sweat analytes on porcine skin) and achieved a linear dynamic range from 0 to 100 mmol/L during fully dynamic continuous flow characterization.
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Affiliation(s)
- Ata Golparvar
- Bio/CMOS Interfaces (BCI) Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), 2000 Neuchatel, Switzerland
| | - Lucie Thenot
- Bio/CMOS Interfaces (BCI) Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), 2000 Neuchatel, Switzerland
| | | | - Sandro Carrara
- Bio/CMOS Interfaces (BCI) Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), 2000 Neuchatel, Switzerland
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Choi S, Sajib MRUZ, Manzano J, Chlebek CJ. mHealth Technology Experiences of Middle-Aged and Older Individuals With Visual Impairments: Cross-Sectional Interview Study. JMIR Form Res 2023; 7:e52410. [PMID: 38145472 PMCID: PMC10775026 DOI: 10.2196/52410] [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: 09/03/2023] [Revised: 11/25/2023] [Accepted: 11/30/2023] [Indexed: 12/26/2023] Open
Abstract
BACKGROUND Current mobile health (mHealth) technology is predominantly designed with a visual orientation, often resulting in user interfaces that are inaccessible to visually impaired users. While mHealth technology offers potential for facilitating chronic illness management and enhancing health behaviors among visually impaired older populations, understanding its usage remains limited. OBJECTIVE This qualitative research aimed to explore the mHealth technology experiences of middle-aged and older individuals with visual impairments including the accessibility and usability issues they faced. METHODS The qualitative exploration was structured using the mHealth for Older Users framework. Cross-sectional interviews were conducted via Zoom between June 1 and July 31, 2023, using an interview protocol for data collection. A thematic analysis approach was employed to analyze the transcribed interview scripts. RESULTS Of the 7 participants who took part in the Zoom interviews, 3 were men and 4 were women, with ages ranging from 53 to 70 years. Most participants adopted mHealth apps and wearable devices for promoting health. They exhibited 3 distinct adoption patterns. Seven themes were emerged from the perceived challenges in using mHealth technologies: (1) a scarcity of accessible user manuals, (2) user interfaces that are not visually impaired-friendly, (3) health data visualizations that are not accessible, (4) unintuitive arrangement of app content, (5) health information that is challenging to comprehend, (6) cognitive overload caused by an excess of audible information, and (7) skepticism regarding the accuracy of health records. mHealth technologies seem to positively affect the health and health management of participants. CONCLUSIONS Design considerations for mHealth technologies should consider individuals' disabilities and chronic conditions and should emphasize the importance of providing accessible manuals and training opportunities when introducing new mHealth solutions.
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Affiliation(s)
- Soyoung Choi
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Md Refat Uz Zaman Sajib
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Jenna Manzano
- College of Liberal Arts and Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Christian Joseph Chlebek
- College of Liberal Arts and Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States
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Slopecki M, Charbonneau M, Lavallière JM, Côté JN, Clément J. Validation of Automatically Quantified Swim Stroke Mechanics Using an Inertial Measurement Unit in Paralympic Athletes. Bioengineering (Basel) 2023; 11:15. [PMID: 38247892 PMCID: PMC10813451 DOI: 10.3390/bioengineering11010015] [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: 11/14/2023] [Revised: 12/14/2023] [Accepted: 12/20/2023] [Indexed: 01/23/2024] Open
Abstract
Biomechanics and training load monitoring are important for performance evaluation and injury prevention in elite swimming. Monitoring of performance and swim stroke parameters is possible with inertial measurement units (IMU) but has not been validated in para-swimmers. The purpose of this study was to validate a single IMU-based system to accurately estimate pool-swam lap time, stroke count (SC), stroke duration, instantaneous stroke rate (ISR), and distance per stroke (DPS). Eight Paralympic athletes completed 4 × 50 m swims with an IMU worn on the sacrum. Strokes cycles were identified using a zero-crossing algorithm on the medio-lateral (freestyle and backstroke) or forward-backward (butterfly and breaststroke) instantaneous velocity data. Video-derived metrics were estimated using Dartfish and Kinovea. Agreement analyses, including Bland-Altman and Intraclass Correlation Coefficient (ICC), were performed on all outcome variables. SC Bland-Altman bias was 0.13 strokes, and ICC was 0.97. ISR Bland-Altman biases were within 1.5 strokes/min, and ICCs ranged from 0.26 to 0.96. DPS Bland-Altman biases were within 0.20 m, and ICCs ranged from 0.39 to 0.93. A single-IMU system can provide highly valid performance and swim stroke monitoring data for elite para-swimmers for the majority of strokes, with the exception of backstroke. Future work should improve bilateral stroke detection algorithms in this population.
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Affiliation(s)
- Matthew Slopecki
- Department of Kinesiology and Physical Education, McGill University, Montréal, QC H2W 1S4, Canada; (J.N.C.); (J.C.)
- Institut National du Sport du Québec, Montréal, QC H1V 3N7, Canada;
| | | | | | - Julie N. Côté
- Department of Kinesiology and Physical Education, McGill University, Montréal, QC H2W 1S4, Canada; (J.N.C.); (J.C.)
| | - Julien Clément
- Department of Kinesiology and Physical Education, McGill University, Montréal, QC H2W 1S4, Canada; (J.N.C.); (J.C.)
- Institut National du Sport du Québec, Montréal, QC H1V 3N7, Canada;
- École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada
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Han Y, Fang X, Li H, Zha L, Guo J, Zhang X. Sweat Sensor Based on Wearable Janus Textiles for Sweat Collection and Microstructured Optical Fiber for Surface-Enhanced Raman Scattering Analysis. ACS Sens 2023; 8:4774-4781. [PMID: 38051949 DOI: 10.1021/acssensors.3c01863] [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: 12/07/2023]
Abstract
Wearable sweat sensors provide real-time monitoring of biomarkers, enabling individuals to gain real-time insight into their health status. Current sensors primarily rely on electrochemical mechanisms, limiting their capacity for the concurrent detection of multiple analytes. Surface-enhanced Raman scattering spectroscopy offers an alternative approach by providing molecular fingerprint information to facilitate the identification of intricate analytes. In this study, we combine a wearable Janus fabric for efficient sweat collection and a grapefruit optical fiber embedded with Ag nanoparticles as a sensitive SERS probe. The Janus fabric features a superhydrophobic side in contact with the skin and patterned superhydrophilic regions on the opposite surface, facilitating the unidirectional flow of sweat toward these hydrophilic zones. Grapefruit optical fibers feature sharp tips with the ability to penetrate transparent dressings. Its microchannels extract sweat through capillary force, and nanoliter-scale volumes of sweat are sufficient to completely fill them. The Raman signal of sweat components is greatly enhanced by the plasmonic hot spots and accumulates along the fiber length. We demonstrate sensitive detection of sodium lactate and urea in sweat with a detection limit much lower than the physiological concentration levels. Moreover, the platform shows its capability for multicomponent detection and extends to the analysis of real human sweat.
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Affiliation(s)
- Yu Han
- Institute of Information Photonics Technology and Faculty of Science, Beijing University of Technology, Beijing 100124, China
| | - Xiaohui Fang
- Institute of Information Photonics Technology and Faculty of Science, Beijing University of Technology, Beijing 100124, China
| | - Hanlin Li
- Institute of Information Photonics Technology and Faculty of Science, Beijing University of Technology, Beijing 100124, China
| | - Lei Zha
- Institute of Information Photonics Technology and Faculty of Science, Beijing University of Technology, Beijing 100124, China
| | - Jinxin Guo
- Institute of Information Photonics Technology and Faculty of Science, Beijing University of Technology, Beijing 100124, China
| | - Xinping Zhang
- Institute of Information Photonics Technology and Faculty of Science, Beijing University of Technology, Beijing 100124, China
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Nourse R, Dingler T, Kelly J, Kwasnicka D, Maddison R. The Role of a Smart Health Ecosystem in Transforming the Management of Chronic Health Conditions. J Med Internet Res 2023; 25:e44265. [PMID: 38109188 PMCID: PMC10758944 DOI: 10.2196/44265] [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: 11/13/2022] [Revised: 06/07/2023] [Accepted: 06/29/2023] [Indexed: 12/19/2023] Open
Abstract
The effective management of chronic conditions requires an approach that promotes a shift in care from the clinic to the home, improves the efficiency of health care systems, and benefits all users irrespective of their needs and preferences. Digital health can provide a solution to this challenge, and in this paper, we provide our vision for a smart health ecosystem. A smart health ecosystem leverages the interoperability of digital health technologies and advancements in big data and artificial intelligence for data collection and analysis and the provision of support. We envisage that this approach will allow a comprehensive picture of health, personalization, and tailoring of behavioral and clinical support; drive theoretical advancements; and empower people to manage their own health with support from health care professionals. We illustrate the concept with 2 use cases and discuss topics for further consideration and research, concluding with a message to encourage people with chronic conditions, their caregivers, health care professionals, policy and decision makers, and technology experts to join their efforts and work toward adopting a smart health ecosystem.
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Affiliation(s)
- Rebecca Nourse
- School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia
| | - Tilman Dingler
- School of Computing and Information Systems, University of Melbourne, Melbourne, Australia
| | - Jaimon Kelly
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Dominika Kwasnicka
- NHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
- Faculty of Psychology, SWPS University of Social Sciences and Humanities, Wroclaw, Poland
| | - Ralph Maddison
- School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia
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Nissen M, Perez CA, Jaeger KM, Bleher H, Flaucher M, Huebner H, Danzberger N, Titzmann A, Pontones CA, Fasching PA, Beckmann MW, Eskofier BM, Leutheuser H. Usability and Perception of a Wearable-Integrated Digital Maternity Record App in Germany: User Study. JMIR Pediatr Parent 2023; 6:e50765. [PMID: 38109377 PMCID: PMC10750977 DOI: 10.2196/50765] [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: 07/12/2023] [Revised: 09/20/2023] [Accepted: 10/02/2023] [Indexed: 12/20/2023] Open
Abstract
Background Although digital maternity records (DMRs) have been evaluated in the past, no previous work investigated usability or acceptance through an observational usability study. Objective The primary objective was to assess the usability and perception of a DMR smartphone app for pregnant women. The secondary objective was to assess personal preferences and habits related to online information searching, wearable data presentation and interpretation, at-home examination, and sharing data for research purposes during pregnancy. Methods A DMR smartphone app was developed. Key features such as wearable device integration, study functionalities (eg, questionnaires), and common pregnancy app functionalities (eg, mood tracker) were included. Women who had previously given birth were invited to participate. Participants completed 10 tasks while asked to think aloud. Sessions were conducted via Zoom. Video, audio, and the shared screen were recorded for analysis. Task completion times, task success, errors, and self-reported (free text) feedback were evaluated. Usability was measured through the System Usability Scale (SUS) and User Experience Questionnaire (UEQ). Semistructured interviews were conducted to explore the secondary objective. Results A total of 11 participants (mean age 34.6, SD 2.2 years) were included in the study. A mean SUS score of 79.09 (SD 18.38) was achieved. The app was rated "above average" in 4 of 6 UEQ categories. Sixteen unique features were requested. We found that 5 of 11 participants would only use wearables during pregnancy if requested to by their physician, while 10 of 11 stated they would share their data for research purposes. Conclusions Pregnant women rely on their medical caregivers for advice, including on the use of mobile and ubiquitous health technology. Clear benefits must be communicated if issuing wearable devices to pregnant women. Participants that experienced pregnancy complications in the past were overall more open toward the use of wearable devices in pregnancy. Pregnant women have different opinions regarding access to, interpretation of, and reactions to alerts based on wearable data. Future work should investigate personalized concepts covering these aspects.
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Affiliation(s)
- Michael Nissen
- Machine Learning and Data Analytics Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Carlos A Perez
- Machine Learning and Data Analytics Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Katharina M Jaeger
- Machine Learning and Data Analytics Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Hannah Bleher
- Department of Social Ethics, University of Bonn, Bonn, Germany
| | - Madeleine Flaucher
- Machine Learning and Data Analytics Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Hanna Huebner
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Nina Danzberger
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Adriana Titzmann
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Constanza A Pontones
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Bjoern M Eskofier
- Machine Learning and Data Analytics Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Heike Leutheuser
- Machine Learning and Data Analytics Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
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48
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Kawai K, Iwamoto K, Miyata S, Okada I, Fujishiro H, Noda A, Nakagome K, Ozaki N, Ikeda M. Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study. J Med Internet Res 2023; 25:e51336. [PMID: 38090797 PMCID: PMC10753421 DOI: 10.2196/51336] [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: 07/31/2023] [Revised: 11/02/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Sleep disturbances are core symptoms of psychiatric disorders. Although various sleep measures have been developed to assess sleep patterns and quality of sleep, the concordance of these measures in patients with psychiatric disorders remains relatively elusive. OBJECTIVE This study aims to examine the degree of agreement among 3 sleep recording methods and the consistency between subjective and objective sleep measures, with a specific focus on recently developed devices in a population of individuals with psychiatric disorders. METHODS We analyzed 62 participants for this cross-sectional study, all having data for polysomnography (PSG), Zmachine, Fitbit, and sleep logs. Participants completed questionnaires on their symptoms and estimated sleep duration the morning after the overnight sleep assessment. The interclass correlation coefficients (ICCs) were calculated to evaluate the consistency between sleep parameters obtained from each instrument. Additionally, Bland-Altman plots were used to visually show differences and limits of agreement for sleep parameters measured by PSG, Zmachine, Fitbit, and sleep logs. RESULTS The findings indicated a moderate agreement between PSG and Zmachine data for total sleep time (ICC=0.46; P<.001), wake after sleep onset (ICC=0.39; P=.002), and sleep efficiency (ICC=0.40; P=.006). In contrast, Fitbit demonstrated notable disagreement with PSG (total sleep time: ICC=0.08; wake after sleep onset: ICC=0.18; sleep efficiency: ICC=0.10) and exhibited particularly large discrepancies from the sleep logs (total sleep time: ICC=-0.01; wake after sleep onset: ICC=0.05; sleep efficiency: ICC=-0.02). Furthermore, subjective and objective concordance among PSG, Zmachine, and sleep logs appeared to be influenced by the severity of the depressive symptoms and obstructive sleep apnea, while these associations were not observed between the Fitbit and other sleep instruments. CONCLUSIONS Our study results suggest that Fitbit accuracy is reduced in the presence of comorbid clinical symptoms. Although user-friendly, Fitbit has limitations that should be considered when assessing sleep in patients with psychiatric disorders.
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Affiliation(s)
- Keita Kawai
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kunihiro Iwamoto
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Seiko Miyata
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Ippei Okada
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Hiroshige Fujishiro
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Akiko Noda
- Department of Biomedical Sciences, Chubu University Graduate School of Life and Health Sciences, Kasugai, Japan
| | - Kazuyuki Nakagome
- Department of Psychiatry, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Norio Ozaki
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
- Pathophysiology of Mental Disorders, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Masashi Ikeda
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
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49
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Yoshida K, Sawano R, Okamoto M, Murao K, Tsuchida S, Terada T. Physical Noninvasive Attacks on Photoplethysmogram by Computer Controlled Blood Pressure Cuff. Sensors (Basel) 2023; 23:9764. [PMID: 38139610 PMCID: PMC10747835 DOI: 10.3390/s23249764] [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: 10/16/2023] [Revised: 11/29/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023]
Abstract
Sensor data has been used in social security and welfare infrastructures such as insurance and medical care to provide personalized products and services; there is a risk that attackers can alter sensor data to obtain unfair benefits. We consider that one of the attack methods to modify sensor data is to attack the wearer's body to modify biometric information. In this study, we propose a noninvasive attack method to modify the sensor value of a photoplethysmogram. The proposed method can disappear pulse wave peaks by pressurizing the upper arm with air pressure to control blood volume. Seven subjects experiencing a rest environment and five subjects experiencing an after-exercise environment wore five different models of smartwatches, and three pressure patterns were performed. It was confirmed in both situations that the displayed heart rate decreased from the true heart rate.
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Affiliation(s)
- Kazuki Yoshida
- Graduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Shiga, Kusatsu 525-8577, Japan; (K.Y.)
| | - Ryota Sawano
- Graduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Shiga, Kusatsu 525-8577, Japan; (K.Y.)
| | - Masahiro Okamoto
- Graduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Shiga, Kusatsu 525-8577, Japan; (K.Y.)
| | - Kazuya Murao
- Graduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Shiga, Kusatsu 525-8577, Japan; (K.Y.)
| | - Shuhei Tsuchida
- Center for Interdisciplinary AI and Data Science, Ochanomizu University, 2-1-1 Otsuka, Bunkyo-ku, Tokyo 112-8610, Japan;
| | - Tsutomu Terada
- Graduate School of Engineering, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Hyogo, Kobe 657-8501, Japan;
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50
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Niggli A, Rothenbühler M, Sachs M, Leeners B. Can Wrist-Worn Medical Devices Correctly Identify Ovulation? Sensors (Basel) 2023; 23:9730. [PMID: 38139575 PMCID: PMC10747116 DOI: 10.3390/s23249730] [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: 11/02/2023] [Revised: 12/03/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023]
Abstract
(1) Background: Hormonal fluctuations across the menstrual cycle lead to multiple changes in physiological parameters such as body temperature, cardiovascular function, respiratory rate and perfusion. Electronic wearables analyzing those parameters might present a convenient alternative to urinary ovulation tests for predicting the fertile window. (2) Methods: We conducted a prospective observational study including women aged 18-45 years without current hormonal therapy who used a wrist-worn medical device and urinary ovulation tests for a minimum of three cycles. We analyzed the accuracy of both the retrospective and prospective algorithms using a generalized linear mixed-effects model. The findings were compared to real-world data from bracelet users who also reported urinary ovulation tests. (3) Results: A total of 61 study participants contributing 205 cycles and 6081 real-life cycles from 3268 bracelet users were included in the analysis. The mean error in identifying ovulation with the wrist-worn medical device retrospective algorithm in the clinical study was 0.31 days (95% CI -0.13 to 0.75). The retrospective algorithm identified 75.4% of fertile days, and the prospective algorithm identified 73.8% of fertile days correctly within the pre-specified equivalence limits (±2 days). The quality of the retrospective algorithm in the clinical study could be confirmed by real-world data. (4) Conclusion: Our data indicate that wearable sensors may be used to accurately detect the periovulatory period.
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Affiliation(s)
- Angela Niggli
- Department of Reproductive Endocrinology, University Hospital of Zürich, Frauenklinikstrasse 10, 8091 Zürich, Switzerland; (M.S.); (B.L.)
- Faculty of Medicine, University of Zurich, 8032 Zurich, Switzerland
| | | | - Maike Sachs
- Department of Reproductive Endocrinology, University Hospital of Zürich, Frauenklinikstrasse 10, 8091 Zürich, Switzerland; (M.S.); (B.L.)
- Faculty of Medicine, University of Zurich, 8032 Zurich, Switzerland
| | - Brigitte Leeners
- Department of Reproductive Endocrinology, University Hospital of Zürich, Frauenklinikstrasse 10, 8091 Zürich, Switzerland; (M.S.); (B.L.)
- Faculty of Medicine, University of Zurich, 8032 Zurich, Switzerland
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