Feature extraction by wavelet transforms to analyze the heart rate variability during two meditation techniques Advances in Numerical Methods
edited by: Nikos Mastorakis, John Sakellaris
In this chapter, we present the analysis of HRV signals by wavelet transform. HRV, described by the extraction of the physiological rhythms embedded within its signal, is the tool through which adaptations of activity of the ANS have been widely studied. The assessment of wavelet transform (WT) as a feature extraction method was used in representing the electrophysiological signals. The purpose of all this is to study the ANS system of subjects who are doing meditation exercises such as the Chi and Yoga. The computed detail wavelet coefficients of the HRV signals were used as the feature vectors representing the signals. These parameters characterize the behavior of the ANS. In order to reduce the dimensionality of the data under study, the statistical parameters were computed.