Key result
A proposed method using discrete wavelet transform successfully localized fundamental heart sounds S1 and S2 from a single seismocardiographic cycle without requiring a reference ECG cycle.
A novel signal processing method allows for the extraction and localization of fundamental heart sounds directly from seismocardiographic signals without needing an ECG reference.
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SCG-based HS extraction may aid valve timing; leaves open prospective clinical validation before adoption.
The phonocardiogram (PCG) signal indicates closing instants of atrio-ventricular and semilunar valves, and this information can also be extracted from two major profiles of a seismocardiographic (SCG) cycle. This letter presents a method to extract fundamental heart sounds (HSs) from a SCG signal. The proposed method employs discrete wavelet transform for signal decomposition, and subsequently, center of gravity (CoG) of power spectrum for each of the subbands is computed. Our method can optimally select wavelet subbands for any combination of sampling frequencies of the signal and number of decomposition levels. Based on proposed CoG criterion, the signal is reconstructed from a number of selected subbands, and instantaneous Hilbert envelope is constructed for localizing peaks of the signal. Finally, a simple decision rule is applied to annotate S1 and S2 sounds of the PCG signal. Experimental results show that the HS waves S1 and S2 can be well localized with the help of one SCG cycle without using a reference ECG cycle.
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Choudhary et al. (2018) studied this question. Heart sound extraction method using discrete wavelet transform and center of gravity of power spectrum was evaluated on Localization of S1 and S2 sounds. A proposed method using discrete wavelet transform successfully localized fundamental heart sounds S1 and S2 from a single seismocardiographic cycle without requiring a reference ECG cycle.
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