Heart Rate Estimation from Ballistocardiogram Using Hilbert Transform and Viterbi Decoding

Abstract

This paper presents a robust algorithm to estimate heart rate (HR) from ballistocardiogram (BCG). The BCG signal can be easily acquired from the vibration or force sensor embedded in a chair or a mattress without any electrode attached to body. The algorithm employs the Hilbert Transform to reveal the frequency content of J-peak in BCG signal. The Viterbi decoding (VD) is used to estimate HR by finding the most likely path through time-frequency state-space plane. The performance of the proposed algorithm is evaluated by BCG recordings from 10 subjects. Mean absolute error (MAE) of 1.35 beats per minute (BPM) and standard deviation of absolute error (STD) of 1.99 BPM are obtained. Pearson correlation coefficient between estimated HR and true HR of 0.94 is also achieved.