Photoplethysmographic based heart rate variability for different physiological conditions

This paper investigates the feasibility of using photoplethysmographic (PPG) signal for heart rate variability (HRV) using different physiological conditions. In this paper, we have analyzed four physiological conditions i.e.; sitting, standing, laying and jogging. The Easy Pulse sensor module was used to pass the signal sensed by the optical sensor through a series of high and low pass filters which later generates a conditioned PPG signal at its output. The Arduino processing module was used for the digitization and processing of the PPG signals. The Arduino program was then developed to capture the PPG data and waveforms. The Kubios HRV software was used to process the PPG data and manipulate it into a HRV format. The PPG signal was then analyzed in time and frequency domain parameters. Later, report sheets were generated based on these analyses. The results showed that the PPG signal as well as HRV changes depending upon the physiological conditions. It was also examined that the low and high frequency components of PPG signal also varied according to the change in physiological condition.