Heart rate variability characterization in daily physical activities using wavelet analysis and multilayer fuzzy activity clustering

Chan, Hsiao-LungHsiao-LungChanFang, Shih-ChinShih-ChinFangKo, Yu-LinYu-LinKoLin, Ming-AnMing-AnLinHUI-HSUN HUANGLin, Chun-HsienChun-HsienLin2023-12-192023-12-192006-010018-9294https://scholars.lib.ntu.edu.tw/handle/123456789/637938A portable data recorder was developed to parallel measure the electrocardiogram and body accelerations. A multilayer fuzzy clustering algorithm was proposed to classify the physical activity based on body accelerations. Discrete wavelet transform was incorporated to retrieve time-varying characteristics of heart rate variability under different physical activities. Nine healthy subjects were included to investigate activity-related heart rate variability during 24 h. The results showed that the heartbeat fluctuations in high frequencies were the greatest during lying and the smallest during standing. Moreover, very-low-frequency heartbeat fluctuations during low activity level (lying) were greater than during high activity level (nonlying).enDiscrete wavelet transform | Fuzzy clustering | Heart rate variability | Physical activityHeart rate variability characterization in daily physical activities using wavelet analysis and multilayer fuzzy activity clusteringjournal article10.1109/TBME.2005.859811164026132-s2.0-30444436757https://api.elsevier.com/content/abstract/scopus_id/30444436757