Pulse wave of human body contains large amount of physiological and pathological information, so the degree of
arteriosclerosis classification algorithm is study based on fuzzy pattern recognition in this paper. Taking the human's
pulse wave as the research object, we can extract the characteristic of time and frequency domain of pulse signal, and
select the parameters with a better clustering effect for arteriosclerosis identification. Moreover, the validity of
characteristic parameters is verified by fuzzy ISODATA clustering method (FISOCM). Finally, fuzzy pattern recognition
system can quantitatively distinguish the degree of arteriosclerosis with patients. By testing the 50 samples in the built
pulse database, the experimental result shows that the algorithm is practical and achieves a good classification
recognition result.
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