Artificial neural networks in computer-assisted classification of heart sounds in patients with porcine bioprosthetic valves

Abstract

The paper describes the design, training and testing of a three-layer feed-forward back-propagation neural network for the classification of bioprosthetic valve closure sounds. Forty-seven patients with a porcine bioprosthetic valve inserted in the aortic position were involved in the study. Twenty-four of them had a normal bioprosthetic valve, and the other 23 had a degenerated valve. Five features extracted from the Fourier spectra and 12 linear predictive coding (LPC) coefficients of the sounds were used separately as the input of two neural-network classifiers. The performance of the classifiers was tested using the leave-one-out method. Results show that correct classifications were 85 per cent using the spectral features, and 89 per cent using the LPC coefficients. The study confirms the potential of artificial networks for the classification of bioprosthetic valve closure sounds. Clinical use of this method, however, still requires further investigation.

Artificial Neural Network–Based Method of Screening Heart Murmurs in Children

“…Efforts to date have met with limited success. 7,11,12,21,[27][28][29][30][31][32] One of these studies examined the sounds from prosthetic heart valves. 11 Several of these studies are simply observations of the time frequency analysis of innocent and pathological heart murmurs, with no emphasis on developing automated diagnostic algorithms.…”

“…7,11,12,21,[27][28][29][30][31][32] One of these studies examined the sounds from prosthetic heart valves. 11 Several of these studies are simply observations of the time frequency analysis of innocent and pathological heart murmurs, with no emphasis on developing automated diagnostic algorithms. 29,30 All of these previous studies (including those using ANNs) have generally focused on determining if a heart murmur exists, with a lack of emphasis on developing diagnostic algorithms differentiating between innocent versus pathological murmurs.…”

“…7 There has been much excitement in the scientific literature in recent years regarding artificial neural networks (ANNs) 8,9 in medicine 10 and, specifically, in cardiology applications. 7,8,[11][12][13][14][15][16][17][18][19][20] ANNs are valuable tools used in complex pattern recognition and classification tasks. They learn complex interactions among inputs and identify relations in input data that may not be apparent to human analysis.…”

“…14 -16,18 -20 There have been several studies on the use of ANNs on heart sounds with limited results and applicability. 7,11,12,21 The aim of the present study was to train an ANN to distinguish between innocent and pathological murmurs effectively.…”

Diagnosing Aortic Valve Stenosis by Parameter Extraction of Heart Sound Signals

“…8,9,11 A stenosis of the aortic valve causes an overload of the heart muscle that leads to a myocardial hypertrophy and a reduced perfusion of the coronary arteries in the long term. An early detection is desirable to avoid a surgical intervention or decrease its extent.…”