Detection of Third Heart Sound Using Variational Mode Decomposition

Abstract

In this paper, a novel approach for the separation of heart and lung sounds (HLS) is proposed based on the nonlinear decomposition technique, variational mode decomposition (VMD) of phonocardiogram signal. Subjective validation and objective quantification are used to assess the performance of the method. The proposed technique is found to perform better than the conventional algorithms such as empirical mode decomposition (EMD), ensemble EMD, and different variants of the EMD. As the third heart sound, $S_{3}$ is an important clinical sign of cardiac failure in elderly patients, a new technique is proposed for its detection. This method is built on the VMD and the smoothed pseudo Wigner–Ville distribution. In total, 40 sets of cardiac cycles containing $S_{3}$ are obtained from publicly available databases and are used to evaluate the performance of the proposed method in noiseless condition. It is able to detect the $S_{3}$ correctly even when the normalized amplitude of $S_{3}$ is 14.1%, whereas the existing method based on the Hilbert variation decomposition requires at least 16.13% of the normalized amplitude of $S_{3}$ in comparison to the normalized amplitude of the highest peak present in the cardiac cycle. In addition to this, the result shows that the proposed method can detect $S_{3}$ in noisy cases up to SNR level of −5 dB.