A fast heart sounds detection and heart murmur classification algorithm

This paper extends our previous studies and presents a fast, automatic cardiac auscultation scoring system that effectively identifies the first and second heart sounds (S₁ and S₂) and extracts clinical features of heart murmurs to assist clinical diagnosis. Using the indices derived from AR modeling, the underlying scoring system is capable of detecting and identifying S₁ and S₂, dissecting the systole and the diastole for further analysis and extracting heart murmurs features found within, such as timing, duration, loudness (intensity), pitch and shape of murmurs. To achieve a broader spectrum of application, only the relative duration difference between systole and diastole was used as the a priori information to identify S₁ and S₂. This algorithm is particularly suited for an embedded system implementation with ease of calculations while maintaining accuracy and effectiveness. The suggested has been successfully evaluated with multiple cardiac cycles, where each systole and diastole was accurately identified and isolated. The performance of the approach has met good success using clinical data from patients with a variety of systolic murmur episodes.