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Comparison of Detrending Methods in Spectral Analysis of Heart Rate Variability

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Author(s): Liping Li | Ke Li | Changchun Liu | Chengyu Liu

Journal: Research Journal of Applied Sciences, Engineering and Technology
ISSN 2040-7459

Volume: 3;
Issue: 9;
Start page: 1014;
Date: 2011;
Original page

Keywords: Empirical mode decomposition | heart rate variability | signal detrending | smoothness priors | wavelet

ABSTRACT
Non-stationary trend in R-R interval series is considered as a main factor that could highly influence the evaluation of spectral analysis. It is suggested to remove trends in order to obtain reliable results. In this study, three detrending methods, the smoothness prior approach, the wavelet and the empirical mode decomposition, were compared on artificial R-R interval series with four types of simulated trends. The Lomb- Scargle periodogram was used for spectral analysis of R-R interval series. Results indicated that the wavelet method showed a better overall performance than the other two methods, and more time-saving, too. Therefore it was selected for spectral analysis of real R-R interval series of thirty-seven healthy subjects. Significant decreases (19.94±5.87% in the low frequency band and 18.97±5.78% in the ratio (p
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