Quantitative analysis of heart sounds and systolic heart murmurs using wavelet transform and AR modeling

A quantitative approach integrating AR modeling and wavelet transform is presented in this paper to analyze the digitized phonocardiogram. The recognition of the first and the second heart sounds (S₁ and S₂) were facilitated with wavelet transform without referring to the QRS waveform. We found that the Daubechies wavelet is most effective in identifying S₁ and S₂. In addition, the boundaries of S₁, S₂, and the onset and duration of the systolic murmur thus identified within the systole could be marked using the wavelet-filtered signal´s strength. Furthermore, quantitative measures derived from a 2^nd order AR model were used to delineate the configuration and pitch of the systolic murmur found within through piecewise segmentation. The proposed approach was tested and proved effective in delineating a set of clinically diagnosed systolic murmurs. The suggested AR and wavelet transform combined approach can be generalized with minor adjustments to delineate diastolic murmurs as well.