Diagnosing aortic valve stenosis by correlation analysis of wavelet filtered heart sounds.

Traditional auscultation performed by the general practitioner remains problematic and often gives significant results only in a late stage of heart valve disease. Valve stenoses and insufficiencies are nowadays diagnosed with accurate but expensive ultrasonic devices. This study aimed to develop a new heart sound analysis method for diagnosing aortic valve stenoses (AVS) based on a wavelet and correlation technique approach. Heart sounds recorded from 373 patients (107 AVS patients, 61 healthy controls (REF) and 205 patients with other valve diseases (OVD)) with an electronic stethoscope were wavelet filtered, and envelopes were calculated. Three correlations on the basis of these envelopes were performed: within the AVS group, between the groups AVS and REF and between the groups AVS and OVD, resulting in the mean correlation coefficients rAVS, rAVSv.REF and rAVSv.OVD. These results showed that rAVS (0.783 +/- 0.097) is significantly higher (p < 0.0001) than rAVSv.REF (0.590 +/- 0.056) and rAVSv.OVD (0.516 +/- 0.056), leading to a highly significant discrimination between the groups. The wavelet and correlation-based heart sound analysis system should be useful to general practitioners for low-cost, easy-to-use automatic diagnosis of aortic valve stenoses.