Automatic detection of cardiac cycle based on an adaptive time-frequency analysis of the phonocardiogram

Abstract

Demonstrates the feasibility of an adaptive time-frequency analysis, the matching pursuit method, to detect each cardiac cycle of the phonocardiogram (PCG). The proposed new method combines a global search of the PCG in terms of energy distribution of the most important components with a local search according to the specific events found within a cardiac cycle. In the PCG recordings of twenty five patients, a detection rate of 96% was achieved. By eliminating the need for the recording of the electrocardiogram as the time-reference signal, this method reduces hardware and software overheads when analysis of PCG signals is primarily aimed. It is believed that, with minor modifications, this method can also be applied to extract different events of the PCG within a cardiac cycle. Furthermore, the procedure described in this paper can be applied to other kind of biomedical signals in order to extract coherent structures and identify specific events.