title: Modeling of heart systolic murmurs based on multivariate matching pursuit for diagnosis of valvular disorders.
abstract: Heart murmurs are pathological sounds produced by turbulent blood flow due to certain cardiac defects such as valves disorders. Detection of murmurs via auscultation is a task that depends on the proficiency of physician. There are many cases in which the accuracy of detection is questionable. The purpose of this study is development of a new mathematical model of systolic murmurs to extract their crucial features for identifying the heart diseases. A high resolution algorithm, multivariate matching pursuit, was used to model the murmurs by decomposing them into a series of parametric time-frequency atoms. Then, a novel model-based feature extraction method which uses the model parameters was performed to identify the cardiac sound signals. The proposed framework was applied to a database of 70 heart sound signals containing 35 normal and 35 abnormal samples. We achieved 92.5% accuracy in distinguishing subjects with valvular diseases using a MLP classifier, as compared to the matching pursuit-based features with an accuracy of 77.5%.
authors: School of Electrical and Computer Engineering, Tarbiat Modares University, P.O. Box 14115-143, Tehran, Iran.
authors: Sepideh
authors: S
authors: Jabbari
authors: Hassan
authors: H
authors: Ghassemian
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D002648:Child; D002675:Child, Preschool; D003936:Diagnosis, Computer-Assisted; D004562:Electrocardiography; D006349:Heart Valve Diseases / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D007223:Infant; D008955:Models, Cardiovascular; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D010701:Phonocardiography / Q000379:methods*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D054160:Systolic Murmurs / Q000503:physiopathology*