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Smartwatch-Based Data Analytics and Feature Selection for Heart Failure Assessment
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Author(s): Xu-Jun Jian (National Taipei University of Technology, Taiwan), Chao-Hung Wang (Chang Gung Memorial Hospital, Taiwan), Tieh-Cheng Fu (Chang Gung Memorial Hospital, Taiwan), Shiyang Lyu (Monash University, Australia), David Taniar (Monash University, Australia)and Tun-Wen Pai (National Taipei University of Technology, Taiwan)
Copyright: 2025
Volume: 16
Issue: 1
Pages: 13
Source title:
International Journal of Mobile Computing and Multimedia Communications (IJMCMC)
Editor(s)-in-Chief: Agustinus Waluyo (Monash University, Australia)
DOI: 10.4018/IJMCMC.371205
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Abstract
Patients with heart failure require long-term or frequent hospitalization, which places a heavy burden on medical resources. The six-minute walk test is a simple and cost-effective method for assessing aerobic capacity and endurance. It does not require specialized personnel or sophisticated equipment and involves recording walking distance, blood pressure, heart rate, and oxygen saturation level within a fixed time interval. In this study, we provided patients with heart failure with a smart watch and an application tool, enabling them to perform the six-minute walk test at home. The application allowed patients to upload their test data on cloud storage, which were examined using feature correlation analysis, regression modeling, and other techniques. The goal was to explore the most influential features that correlated with outpatient records and provide effective reminders to patients with heart failure to monitor their health status during their daily lives, which would reduce medical resource consumption.
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