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Regularity Measures for Autonomic Nervous System Data: Pseudoentropy as a Dynamic Marker

Pinto, R.

Regularity Measures for Autonomic Nervous System Data: Pseudoentropy as a Dynamic Marker, Proc IASTED Conf. on Signal and Image Processing, Dallas, United States, Vol. 759-052, pp. 759-052 - 759-052, December, 2011.

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Abstract
The study of heart rate variability founds the foremost way to access to the role of the autonomic nervous system (ANS) in cardiovascular regulation, in order to understand physiological process in the homeostasis maintenance. In last years, several signal processing methods were proposed to understand the influence of the two main branches of the autonomic nervous system (sympathetic nervous system and vagal nervous system), based in time, frequency and time-frequency methods, whose data is extracted in ECG records obtained in subjects during standard autonomic tests. Time-frequency methods constitute a great advance to process this data, as they are suitable for nonstationarity, as is the case. However studies with too short records may present some constrains. Methods from chaos theory have been recently used to the study of the ANS, and by using this approach other non-classical measures of autonomic regulation are brought forward. In this work two psedoentropy measures are presented and tested in heart rate variability and blood pressure data, using short time series extracted from two phases of the head-up-tilt test.