Nonintrusive heart rate measurement using ballistocardiogram signals: a comparative study

Abstract

Nonintrusive monitoring and long-term monitoring of vital signs are essential requirements for early diagnosis and prevention due to many reasons, one of the most important being improving the quality of life. In this paper, we present a comparative study using various algorithms, i.e., wavelet analysis, cepstrum, fast Fourier transform, and autocorrelation function for heart rate measurement. The heart rate was measured from noisy ballistocardiogram signals acquired from 50 subjects in a sitting position using a massage chair. The signals were unobtrusively collected from a microbend fiber-optic sensor embedded within the headrest of the chair and then transmitted to a computer through a Bluetooth connection. The multiresolution analysis of the maximal overlap discrete wavelet transform was implemented for heart rate measurement. The error between the proposed method and the reference electrocardiogram is estimated in beats per minute using the mean absolute error in which the system achieved relatively good results ( $$10.12\pm 4.69$$ ) despite the remarkable amount of motion artifact produced owing to the frequent body movements and/or vibrations of the massage chair during stress relief massage. In contrast, the error between the proposed method and the reference signal was very large when other algorithms, i.e., cepstrum, fast Fourier transform, and autocorrelation function, were implemented for heart rate measurement.