ABSTRACT
Segmentation of fundamental heart sounds–S1 and S2 is important for automated monitoring of cardiac activity including diagnosis of the heart diseases. This pa-per proposes a novel hybrid method for S1 and S2 heart sound segmentation using group 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 of PCG signals. The denoised GS-PCG signals are then decomposed into subsequent modes with specific spectral characteristics using VMD algorithm. The appropriate mode for further processing is selected based on mode central frequencies and mode energy. It is then followed by the extraction of Hilbert envelope (HEnv) and a thresholding on the selected mode to segment S1 and S2 heart sounds. The performance advantage of the proposed method is verified using PCG signals from benchmark databases namely eGeneralMedical, Littmann, Washington, and Michigan. The proposed hybrid algorithm has achieved a sensitivity of 100%, positive predictivity of 98%, accuracy of 98% and detection error rate of 1.5%. The promising results obtained suggest that proposed approach can be considered for automated heart sound segmentation.
Subject(s)
Benchmarking , Diagnosis , Heart Diseases , Heart Sounds , Heart , Methods , Michigan , WashingtonABSTRACT
Purpose: The purpose of this study is to develop methods to identify glaucoma by examining the optic nerve head (ONH) of donor’s eyes when information on the preexisting ocular disease is unavailable. Materials and Methods: The ONH of the donor’s eyes was evaluated under a stereomicroscope for the cup‑disc ratio (CDR) and focal retinal rim thinning. The vertical diameter of the cup and disc was also measured using a precalibrated eyepiece micrometer. The suspect eyes were subjected to histological analysis to confirm the presence of specific glaucomatous changes. Results: A total of 202 eyes from 119 donors (68 males and 51 females, aged 42–96) were evaluated for glaucoma. Among them, 190 (94%) eyes showing vertical CDR in the of 0.0–0.6 range were considered nonglaucomatous and the remaining eyes with >0.6 as glaucoma suspect. The calculated mean CDR of the two groups (0.3 ± 0.16, 0.62 ± 0.27) was highly significant (P = 0.0003). Of 12 eyes suspected of glaucoma, 7 eyes from 5 donors showed specific glaucomatous changes by histology. The prevalence of glaucoma was 4.2% among the donors studied. Conclusions: A simple method of screening fresh donor eyes for selecting those with glaucoma features using CDR and histological analysis was reported. This method helps to obtain biologically active human ocular tissue for glaucoma research on gene expression, ultrastructural/proteome changes, and outflow mechanism.