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- 저자 : V. G. Sujadevi (검색결과 1 건)
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V. G. Sujadevi,Neethu Mohan,S. Sachin Kumar,S. Akshay,K. P. Soman 대한의용생체공학회 2019 Biomedical Engineering Letters (BMEL) Vol.9 No.4
Segmentation of fundamental heart sounds–S1 and S2 is important for automated monitoring of cardiac activity includingdiagnosis of the heart diseases. This pa-per proposes a novel hybrid method for S1 and S2 heart sound segmentation usinggroup sparsity denoising and variation mode decomposition (VMD) technique. In the proposed method, the measured phonocardiogram(PCG) signals are denoised using group sparsity algorithm by exploiting the group sparse (GS) property ofPCG signals. The denoised GS-PCG signals are then decomposed into subsequent modes with specifi c spectral characteristicsusing VMD algorithm. The appropriate mode for further processing is selected based on mode central frequencies and modeenergy. It is then followed by the extraction of Hilbert envelope (HEnv) and a thresholding on the selected mode to segmentS1 and S2 heart sounds. The performance advantage of the proposed method is verifi ed using PCG signals from benchmarkdatabases namely eGeneralMedical, Littmann, Washington, and Michigan. The proposed hybrid algorithm has achieved asensitivity of 100%, positive predictivity of 98%, accuracy of 98% and detection error rate of 1.5%. The promising resultsobtained suggest that proposed approach can be considered for automated heart sound segmentation.
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