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Analysis of Heart Rate Variability Via Health Care Platform

Author

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  • Yong-Hong Hsu

    (Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan)

  • Yang-Yi Chen

    (Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan)

  • Chun-Liang Lin

    (Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan)

  • Changchen Zhao

    (Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan School of Automation Science and Electrical Engineering, Beihang University, Beijing)

Abstract

This research task develops a mobile healthcare analysis system (PHAS) which combines both easy ECG signal measurement and reliable analysis of heart rate variability for home care purpose. The PHAS is composed by a health care platform (HCP) and a data system analysis (DSA) module. The HCP consists of a self-developed two pole electrocardiography (ECG) measuring device and the DSA a data processing unit for detection and analysis of heart rate variability. For the DSA module, the adaptive R Peak detection algorithm is proposed to reliably detect the R peak of ECG for HRV analysis. A number of features are extracted from ECG signals. A data mining method is employed for HRV analysis to exploit the correlation between HRV and these features. Experiments are conducted by establishing a database of ECG signals measured from 29 subjects under rest and exercise condition. The results show the PHAS’s significant potential in mobile applications of personal daily health care.

Suggested Citation

  • Yong-Hong Hsu & Yang-Yi Chen & Chun-Liang Lin & Changchen Zhao, 2017. "Analysis of Heart Rate Variability Via Health Care Platform," International Journal of Healthcare and Medical Sciences, Academic Research Publishing Group, vol. 3(12), pages 103-116, 12-2017.
    • Handle: RePEc:arp:ijohms:2017:p:103-116
    DOI: arpgweb.com/?ic=journal&journal=13&info=aims
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