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In this paper, a new efficient feature extraction method based on theadaptive threshold of wavelet package coefficients is presented. This paperespecially deals with the assessment of autonomic nervous system using thebackground variation of the signal Heart Rate Variability HRV extracted fromthe wavelet package coefficients. The application of a wavelet packagetransform allows us to obtain a time-frequency representation of the signal,which provides better insight in the frequency distribution of the signal withtime. A 6 level decomposition of HRV was achieved with db4 as mother wavelet,and the above two bands LF and HF were combined in 12 specialized frequenciessub-bands obtained in wavelet package transform. Features extracted from thesecoefficients can efficiently represent the characteristics of the originalsignal. ANOVA statistical test is used for the evaluation of proposedalgorithm.

Heart Rate Variability Analysis Using Threshold of Wavelet Package Coefficients