Non-linear analysis of heart rate variability

Abstract

HRV signals can be viewed as discrete time series and treated as well through accepted mathematical procedures in order to find specific properties. These mathematical procedures can be linear or non-linear. Lately, non-linear analysis methods brought new and valuable results in HRV analysis and prediction. This paper deals with approximate entropy and sample entropy calculations in order to find unrevealed properties of these signals. The used signals are obtained from the MIT-BIH Long-term ECG database. The aim of this paper is to measure information theory based parameters as different entropies for different signals to emphasize non-linear dynamics in HRV in order to help cardiology specialists.