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Abstract
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Article Information:
Comparison of Detrending Methods in Spectral Analysis of Heart Rate Variability
Liping Li, Ke Li, Changchun Liu and Chengyu Liu
Corresponding Author: Liping Li
Submitted: 2011 July, 20
Accepted: 2011 September, 07
Published: 2011 September, 20 |
Abstract:
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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<0.001)) were found. Thus
the wavelet method is recommended as an optimal choice for use.
Key words: Empirical mode decomposition, heart rate variability, signal detrending, smoothness priors, wavelet, ,
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Cite this Reference:
Liping Li, Ke Li, Changchun Liu and Chengyu Liu, . Comparison of Detrending Methods in Spectral Analysis of Heart Rate Variability. Research Journal of Applied Sciences, Engineering and Technology, (09): 1014-1021.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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