Segmentation of heart rate variability in different physical activities

Heart rate variability is due to the interaction of sympathetic and parasympathetic nervous system. The spectral analysis of HRV provides a noninvasive probe to assess the function of the autonomic nervous system. The recording of physiological signals on free-moving subjects provides a useful tool to evaluate the autonomic states in the daily activities, but the information of activities is lack in the conventional ECG Holter, so it is difficult to estimate HRV in different activities. In this paper, we developed a microcontroller-based system for ECG and physical-activity recording system. The acceleration signals located at chest and thigh is used to classify the basic activities, including lying (supine, left lateral, right lateral, and prone), sitting, standing, and dynamic activity. Time-frequency analysis is used to compute the time-varying spectra of heart rate variability. In the 24-hour recording, the high-frequency fluctuations are the largest and the second in the sitting, which means major dominance of parasympathetic tone. As the posture is changing form sitting to standing and dynamic activity, the low-frequency power to high-frequency power ratio increases which demonstrates the increase of sympathetic tone and decrease of parasympathetic tone.