In vitro and in vivo low frequency acoustic analysis of Bjork-Shiley convexo-concave heart valve opening sounds

A pattern recognition method using diagnostic features from the low frequency spectra of Bjork-Shiley convexo concave (BSCC) valve opening sounds was tested for differentiating intact valves from those having a single leg separation (SLS) of the outlet strut. The method was applied to valve opening sounds obtained from a pulse duplicator system (6 intact and 6 SLS valves) and recorded in sheep (11 intact and 16 SLS valves). A total of 30 opening sounds were analyzed for each sheep and 10 opening sounds for each pulse duplicator test. For each valve, 21 diagnostic features were extracted from the mean power spectrum of the opening sounds for training and testing the K-nearest neighbor and the Bayes classifiers. All combinations of 1, 2, 3 and 4 features among 21 were evaluated to find the most discriminant feature sets. For the in vitro study, 100% of correct classifications (CCs) was obtained with several feature sets and either classifier. For the sheep study, 93% of CCs was obtained with two feature sets and the Bayes classifier. The feature set that could best classify both in-vivo and in-vitro valve opening sound spectra provided 82% of CCs. The in vitro and in vivo studies thus demonstrated that the low frequency analysis of BSCC opening sounds is a promising method of detecting SLS of BSCC mitral valves