Analysis of Heart Rate Variability Via Health Care Platform

Yong-Hong Hsu, Yang-Yi Chen, Chun-Liang Lin and Changchen Zhao
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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

International Journal of Healthcare and Medical Sciences, 2017, vol. 3, issue 12, 103-116

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.

Keywords: Electrocardiography; Heart rate variability; Health care platform; Data processing; Home care application. (search for similar items in EconPapers)
Date: 2017
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