Heart auscultation is a widely used technique for diagnosing cardiac abnormalities. In that context, capturing of phonocardiogram (PCG) signals and automatically monitoring of the heart by identifying S1 and S2 complexes is an emerging ?eld. One of the ?rst steps involved for identifying S1–S2 complexes is detection of the locations of these events in the PCG signals. In the literature, the methods to detect these events in the PCG signal have largely focused on exploiting the dominant low frequency characteristics of the S1–S2 complexes through frequency–domain processing. In this paper, we propose a purely time–domain processing based method that employs a heavily decaying low pass ?lter (referred to as zero frequency ?lter) to suppress extraneous factors and detect S1–S2 locations. We demonstrate the potential of the proposed approach through investigations on two publicly available data sets, namely the PASCAL heart sounds challenge 2011 (PHSC–2011) and PhysioNet CinC. The method is also evaluated through an analysis with wearable sensors in the presence and absence of speech activity.
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona (ES), pp. 1254-1258