Automated Pattern Classification for Pcg Signal Based on Adaptive Spectral K-means Clustering Algorithm
نویسندگان
چکیده
PCG signal pattern classification, also known as auscultation pattern recognition, was one of the efficient computer-based methods applied to medical decision making. PCG Pattern recognition generally is interpreted in two ways. The most general definition includes recognition of patterns in any type of PCG dataset and is called uniform PCG pattern classification this discriminate peaks of heart sounds as excitation source for circulation hemodynamic, and other is called adaptive pattern clustering which magnify and observe the spectral characteristics associated with PCG waveform turbulences and differentiate them as clinical diagnostic indices. Fig.1 shows how the four heart sounds are correlated to the electrical and mechanical events of the cardiac cycle.
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