Heart rate variability (HRV) measures the instantaneous change in heart rate and is an important marker for checking physical condition as well as mental stress of a person. In this paper, we propose a methodology to calculate HRV of a person using smart phone audio. Heart sound is captured in the inbuilt microphone of a smart phone, by placing the device on the chest of the person. We propose a process flow to make the phone captured noisy audio signal clean and audible. Furthermore, we propose a novel peak detection algorithm for accurately locating the peaks corresponding to heart sound in the noisy audio signal. The algorithm is also capable of rejecting the noisy peaks present in the captured audio that resembles heart sound pattern. Results show that the proposed methodology yields significant improvement in estimating HRV parameters compared to a clinical pulse-oximeter device, that works on the principle of photoplethysmogram (PPG) technique.
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