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

Hsiao Lung Chan; Shih Chin Fang; Yu Lin Ko; Ming An Lin; Hui Hsun Huang; Chun Hsien Lin

doi:10.1109/TBME.2005.859811

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

Hsiao Lung Chan^*, Shih Chin Fang, Yu Lin Ko, Ming An Lin, Hui Hsun Huang, Chun Hsien Lin

^*Corresponding author for this work

Research output: Contribution to journal › Journal Article › peer-review

27 Scopus citations

Abstract

A 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).

Original language	English
Pages (from-to)	133-139
Number of pages	7
Journal	IEEE Transactions on Biomedical Engineering
Volume	53
Issue number	1
DOIs	https://doi.org/10.1109/TBME.2005.859811
State	Published - 01 2006

Keywords

Discrete wavelet transform
Fuzzy clustering
Heart rate variability
Physical activity

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10.1109/TBME.2005.859811

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

abstract = "A 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).",

keywords = "Discrete wavelet transform, Fuzzy clustering, Heart rate variability, Physical activity",

author = "Chan, {Hsiao Lung} and Fang, {Shih Chin} and Ko, {Yu Lin} and Lin, {Ming An} and Huang, {Hui Hsun} and Lin, {Chun Hsien}",

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AU - Chan, Hsiao Lung

AU - Fang, Shih Chin

AU - Ko, Yu Lin

AU - Lin, Ming An

AU - Huang, Hui Hsun

AU - Lin, Chun Hsien

PY - 2006/1

Y1 - 2006/1

N2 - A 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).

AB - A 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).

KW - Discrete wavelet transform

KW - Fuzzy clustering

KW - Heart rate variability

KW - Physical activity

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

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Keywords

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