期刊
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
卷 8, 期 6, 页码 542-550出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.bspc.2013.05.006
关键词
Heart rate variability; Wavelet transform; Wavelet packets; RHRV
资金
- European Regional Development Fund (ERDF/FEDER) of the Galician Ministry of Education [CN2012/151]
One of the most promising non-invasive markers of the activity of the autonomic nervous system is heart rate variability (HRV). HRV analysis toolkits often provide spectral analysis techniques using the Fourier transform, which assumes that the heart rate series is stationary. To overcome this issue, the Short Time Fourier Transform (STFT) is often used. However, the wavelet transform is thought to be a more suitable tool for analyzing non-stationary signals than the STFT. Given the lack of support for wavelet-based analysis in HRV toolkits, such analysis must be implemented by the researcher. This has made this technique underutilized. This paper presents a new algorithm to perform HRV power spectrum analysis based on the Maximal Overlap Discrete Wavelet Packet Transform (MODWPT). The algorithm calculates the power in any spectral band with a given tolerance for the band's boundaries. The MODWPT decomposition tree is pruned to avoid calculating unnecessary wavelet coefficients, thereby optimizing execution time. The center of energy shift correction is applied to achieve optimum alignment of the wavelet coefficients. This algorithm has been implemented in RHRV, an open-source package for HRV analysis. To the best of our knowledge, RHRV is the first HRV toolkit with support for wavelet-based spectral analysis. (C) 2013 Elsevier Ltd. All rights reserved.
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