Background: Implementing exercises in the form of video games, otherwise known as exergaming, has gained recent attention as a way to combat health issues resulting from sedentary lifestyles. However, these exergaming apps have not been developed for exercises that can be performed in wheelchairs, and they tend to rely on whole-body movements.
Objective: This study aims to develop a mobile phone app that implements electromyography (EMG)-driven exergaming, to test the feasibility of using this app to enable people in wheelchairs to perform exergames independently and flexibly in their own home, and to assess the perceived usefulness and usability of this mobile health system.
Methods: We developed an Android mobile phone app (Workout on Wheels, WOW-Mobile) that senses upper limb muscle activity (EMG) from wireless body-worn sensors to drive 3 different video games that implement upper limb exercises designed for people in wheelchairs. Cloud server recordings of EMG enabled long-term monitoring and feedback as well as multiplayer gaming. Bench testing of data transmission and power consumption were tested. Pilot testing was conducted on 4 individuals with spinal cord injury. Each had a WOW-Mobile system at home for 8 weeks. We measured the minutes for which the app was used and the exergames were played, and we integrated EMG as a measure of energy expended. We also conducted a perceived usefulness and usability questionnaire.
Results: Bench test results revealed that the app meets performance specifications to enable real-time gaming, cloud storage of data, and live cloud server transmission for multiplayer gaming. The EMG sampling rate of 64 samples per second, in combination with zero-loss data communication with the cloud server within a 10-m range, provided seamless control over the app exergames and allowed for offline data analysis. Each participant successfully used the WOW-Mobile system at home for 8 weeks, using the app for an average of 146 (range 89-267) minutes per week with the system, actively exergaming for an average of 53% of that time (39%-59%). Energy expenditure, as measured by integrated EMG, was found to be directly proportional to the time spent on the app (Pearson correlation coefficient, r=0.57-0.86, depending on the game). Of the 4 participants, 2 did not exercise regularly before the study; these 2 participants increased from reportedly exercising close to 0 minutes per week to exergaming 58 and 158 minutes on average using the WOW-Mobile fitness system. The perceived usefulness of WOW-Mobile in motivating participants to exercise averaged 4.5 on a 5-point Likert scale and averaged 5 for the 3 participants with thoracic level injuries. The mean overall ease of use score was 4.25 out of 5.
Conclusions: Mobile app exergames driven by EMG have promising potential for encouraging and facilitating fitness for individuals in wheelchairs who have maintained arm and hand mobility.
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http://dx.doi.org/10.2196/16054 | DOI Listing |
EBioMedicine
December 2024
Department of Anaesthesiology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands.
Background: Clinical decision-making is increasingly shifting towards data-driven approaches and requires large databases to develop state-of-the-art algorithms for diagnosing, detecting and predicting diseases. The intensive care unit (ICU), a data-rich setting, faces challenges with high-frequency, unstructured monitor data. Here, we showcase a successful example of a data pipeline to efficiently move patient data to the cloud environment for structured storage.
View Article and Find Full Text PDFSci Rep
December 2024
Computer Engineering Department, UET Taxila, Rawalpindi, Punjab, 47050, Pakistan.
IoT device security has become a major concern as a result of the rapid expansion of the Internet of Things (IoT) and the growing adoption of cloud computing for central monitoring and management. In order to provide centrally managed services each IoT device have to connect to their respective High-Performance Computing (HPC) clouds. The ever increasing deployment of Internet of Things (IoT) devices linked to HPC clouds use various medium such as wired and wireless.
View Article and Find Full Text PDFJ Imaging
December 2024
Department of Mechatronics Engineering, Universidad Católica Boliviana "San Pablo", La Paz 4807, Bolivia.
Computer vision-based gait recognition (CVGR) is a technology that has gained considerable attention in recent years due to its non-invasive, unobtrusive, and difficult-to-conceal nature. Beyond its applications in biometrics, CVGR holds significant potential for healthcare and human-computer interaction. Current CVGR systems often transmit collected data to a cloud server for machine learning-based gait pattern recognition.
View Article and Find Full Text PDFJMIR Med Inform
December 2024
Center for Geriatrics & Gerontology, Taichung Veterans General Hospital, 1650 Taiwan Boulevard Sect 4, Taichung, 407219, Taiwan, 886 4-2359-2525, 886 4-2359-5046.
Background: Telehealth programs and wearable sensors that enable patients to monitor their vital signs have expanded due to the COVID-19 pandemic. The electronic National Early Warning Score (e-NEWS) system helps identify and respond to acute illness.
Objective: This study aimed to implement and evaluate a comprehensive telehealth system to monitor vital signs using e-NEWS for patients receiving integrated home-based medical care (iHBMC).
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue
November 2024
Department of Nursing, the Second Affiliated Hospital of Dalian Medical University, Dalian 116027, Liaoning, China. Corresponding author: Chen Shuliang, Email:
Objective: To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their families, and provide data support for clinical decision-making.
Methods: A retrospective study was conducted. The clinical information of stroke patients (n = 53 793) were extracted from the Yidu cloud big data server system of the Second Affiliated Hospital of Dalian Medical University from January 1, 2001 to July 31, 2023.
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