Comparison of Heart Rate Variability Analysis with Empirical Mode Decomposition and Fourier Transform

JAVIER ZELECHOWER; MARCELO RISK; FRANCISCO REDELICO; POSE, FERNANDO

Communications in Computer and Information Science

Springer Nature

Año: 2021; p. 278 - 289

The heart rate variability (HRV) analysis allows the study ofthe regulation mechanisms of the cardiovascular system, in both normaland pathological conditions, and the power spectral density analysis ofthe short-term HRV was adopted as a tool for the evaluation of the autonomicfunction. The Ensemble Empirical Mode Decomposition (EEMD)is an adaptive method generally used to analyze non-stationary signalsfrom non-linear systems. In this work, the performance of the EEMD inthe decomposition of the HRV signal in the main spectral components isstudied, in a first instance to a synthesized series to calibrate the methodand achieve confidence and then to a real HRV database. In conclusion,the results of this work propose the EEMD as useful method for analysisHRV data. The ability of decomposes the main spectral bands and thecapability to deal with non-linear and non-stationary behaviors makesthe EEMD a powerful method for tracking frequency changes and amplitudemodulations in HRV signals generated by autonomic regulation.