HRV Analysis of Different Postures of Young Healthy Women Using Signal Processing Methods

The variations in the intervals of successive heartbeats, i.e. between the two R peaks are known as Heart Rate Variability (HRV). HRV is used for identifying the physiological and pathological cardiac functioning of the heart. The characteristics of HRV are changing continuously in the various physical activities such as a change in postures from supine to standing. Therefore, the main objective of this paper is to investigate the autonomic regulations of cardiac activity in the lying and standing postures. The HRV signals of 20 young healthy women were measured during supine and standing postures using BIOPAC[Formula: see text] MP150 system. The frequency-domain methods using the Autoregressive (AR) Model and nonlinear methods such as Sample Entropy (SampEn) and Approximate Entropy (ApEn) were used to calculate the posture-related differences in HRV. The Box and Whisker plots are used for representing the distribution of frequency-domain methods and nonlinear methods. Further, paired t-tests were used for validating the statistically significant values. It is concluded from the results that the heart rate is significantly higher and HRV is lower in the standing posture ([Formula: see text]) as compared to the supine posture. Lower HRV in the standing posture implies that sympathetic activities were higher and parasympathetic activities were lower in comparison to the supine postures.