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An algorithm for segmentation of heart sounds (HSs) into a single cardiac cycle (Sl-Systole-S2-Diastole) using homomorphic filtering and k-means clustering and a three way classification of heart sounds into normal (N), systolic murmur (S), and diastolic murmur (D), based on neural networks is developed. This algorithm does not require additional reference signal such as ECG signal. Feature vectors...
A segmentation algorithm, which detects a single cardiac cycle (S 1-systole-S2-diastole) of phonocardiogram (PCG) signals using homomorphic filtering and K-means clustering and a three way classification of heart sounds into normal (N), systolic murmur (S) and diastolic murmur (D) using grow and learn (GAL) neural network, are presented. Homomorphic filtering converts a non-linear combination of signals...
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