CARDIOVASCULAR PULSE WAVE ANALYSIS METHOD AND SYSTEM

摘要

Factor retrieving is a major approach for pulse wave analysis. Stiffness index and cardiac output are widely used factors for cardiac risk detection. Research has been done on clinical pulse wave data which are collected by pulse oximeter. The result shows that collected factors have a positive correlation with certain cardiac risks. Some adjustments have been applied on the algorithms that increase the significance. In addition to the factor based analysis, other signal processing techniques for pulse waveforms are included such as bispectrum estimation, Wavelet transform, and weighted dynamic time warping. Bispectrum estimation and Wavelet transform have meaningful features of pulse waveforms with some special shapes. Weighted dynamic time warping compares the similarity of waveforms. It also includes medical significance into the calculation by adjusting the weight vector. This algorithm has higher accuracy when providing more samples to compare. The factor based analysis and waveform analysis compose an analytic model which can be used for risk evaluation, classification and disease detection.