Myocardial Ischemia Detection by Pulse Signal Features and Fuzzy Clustering

The aim of this study is to propose a new diagnosing algorithm, for myocardial ischemia, based on the newly developed non-invasive measurement, three-axis sphygmography, and further processed by modified fuzzy c-means algorithms. The three-axis sphygmography measures pressure pulse waveform (PPW), and the PPW are analyzed by its harmonic components in the frequency domain. The first three harmonics of the Fourier series of PPW are significantly different between myocardial ischemia patients and normal subjects. The harmonic of the Fourier series of PPW are feed into a modified fuzzy c-means algorithm, and developed PPW criteria to identify myocardial ischemia with sensitivity 69% and specificity 100%.