Heart Rate Detection from Ballistocardiogram Using Continuous Wavelet Transformation

In this paper we present an algorithm for identifying individual heart beats from ballistocardiogram (BCG) records as part of IFMBE Scientific Challenge for ICBHI 2022. The main purpose of this challenge is to explore and test new algorithms of BCG signal processing for heart beat detection from BCG signal. The BCG signal records dataset included records of healthy subjects and also of patients previously diagnosed with atrial fibrillation (AF). An electrocardiogram (ECG) was acquired simultaneously for reference. The R peaks of the ECG signal were annotated as a reference, with the goal of detecting the J peaks of BCG signal which correspond to these R peaks. Our approach to this challenge consisted of two different algorithms. A comparison between using peak detection of a BCG signal only in the time domain and both in time and frequency domain using continuous wavelet transform (CWT) was made. Apart from the local maxima, the local minima were also detected, and later used for extraction of possible motion artifacts. The results showed that using CWT provided better J peak detection, and therefore better heart rate detection than regular time domain method.