Automatic phonocardiograph signal analysis for detecting heart valve disorders

A novel method for discrimination between innocent and pathological heart murmurs

“…artificial neural network. However, the SVM is favored to this study due to its immunity to the local minimums since only the boundary vectors contribute to the training, as has been reported in other related studies [33,36,52].…”

“…This can incorporate irrelevant frequency bands, increase dimension of the feature vector and therefor increase the structural risk of the classifier. Several studies were conducted to explore and compare different wavelet families [31][32][33], time-frequency representations (TFR) [34][35][36][37][38], and TFRs together with two-frequency representation [39] as the mathematical tools for feature extraction from heart murmurs. Although these studies suggested mathematical methods for the murmur classification, stability of their suggested methods was not validated for the IM class, as IM was not included in their data material.…”

Heart Diseases Diagnosis Using Intelligent Algorithm Based on PCG Signal Analysis

“…Several researches, various methodologies and many tools that had been proposed were used in recently published papers for medical systems development for heart diseases diagnosis [8] [9] [10]. Unfortunately, the achieved accuracy was not satisfactory so, the work is devoted to proposing an algorithm for heart diseases diagnosis with high accuracy.…”

Heart Sound Anomaly and Quality Detection using Ensemble of Neural Networks without Segmentation

“…Several studies have been conducted to PCG segmentation using different envelope extraction methods such as Shannon energy [2], Shannon entropy [3], HilbertHuang transform [4], and autocorrelation [5]. The envelope of signal attenuates the noise and amplifies the low-intensity components of the signal.…”

“…to address these shortcomings in a cost-effective diagnostic tests in ambulatory monitoring, several techniques [2][3][4][5] have been proposed for automatic analysis of heart sounds.…”