Smartwatch-Based Data Analytics and Feature Selection for Heart Failure Assessment

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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Publication Details

Journal
International Journal of Mobile Computing and Multimedia Communications
Published
2025-03-12
DOI
https://doi.org/10.4018/ijmcmc.371205
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Smartwatch-Based Data Analytics and Feature Selection for Heart Failure Assessment

Shiyang Lyu, Tieh‐Cheng Fu, David Taniar, Tun‐Wen Pai et al.
International Journal of Mobile Computing and Multimedia Communications
Artificial Intelligence in Healthcare
article

Smartwatch-Based Data Analytics and Feature Selection for Heart Failure Assessment

Shiyang Lyu, Tieh‐Cheng Fu, David Taniar, Tun‐Wen Pai, Chao‐Hung Wang, X. Jian
article en

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.

International Journal of Mobile Computing and Multimedia CommunicationsVol. 16(1)
National Taipei University of Technology (TW), Chang Gung Memorial Hospital (TW), Monash University (AU)
Openalex Percentile: Top 95%
Artificial Intelligence in Healthcare
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Smartwatch-Based Data Analytics and Feature Selection for Heart Failure Assessment — Shiyang Lyu, Tieh‐Cheng Fu, et al. · International Journal of Mobile Computing and Multimedia Communications (2025) | TGRS Research Map | TGRS