A Developed Zeeman Model for HRV Signal Generation in Different Stages of Sleep

Abstract

Heart Rate Variability (HRV) is a sophisticated measure of an important and fundamental aspect of an individual's physiology. Heart rate variability (HRV) measurement is an important tool in cardiac diagnosis that can provide clinicians and researchers with a 24-hour noninvasive measure of autonomic nervous system activity. Heart Rate Variability is analyzed in two ways, either over time (Time Domain) or in terms of the frequency of changes in heart rate (Frequency Domain). Preliminarily studying on the different effects of sleep on HRV signal can be useful for finding out the function of autonomic nervous system (ANS) on heart rate. In this paper, we consider a HRV signal for one normal person in different sleep stages: stage1, stage2, stage3 and REM. Therefore, we use FFT on HRV signal and show differences in various stages. In addition, we evaluate these differences in quantitative and qualitative. This model can be used as a basic one for developing models to generate artificial HRV signal.