Spectral characterization and classification of Carpentier-Edwards heart valves implanted in the aortic position.

This paper demonstrates an improvement in the performance of spectral phonocardiography, combined with pattern recognition techniques for monitoring the condition of bioprosthetic heart valves. The analysis of the heart sounds is performed using a modified forward-backward overdetermined Prony's method. Results show that the condition of the bioprosthesis affects mostly the higher part of the spectrum (i.e., above 250 Hz) where no frequency components were found for malfunctioning cases. Therefore, the amplitudes of the three highest frequency components are used as the input vector of an adaptive single layer perceptron-based classifier to identify normal and malfunctioning classes. For the sample set examined, this method gives 100% correct discrimination between normal and malfunctioning Carpentier-Edwards (C-E) valves.