Research And Application Of Human Pulse Detection

Cardiovascular disease is one of serious diseases which threat people's health and life, which can be reflected by a comprehensive parameter- human pulse wave. Even thought many clinical approaches are applied to detect cardiovascular disease, the painful expensive, painful and sophisticated bring much inconvenient to the patients. Therefore, it is important in both theory and application to research the non-invasive method for diagnosing the cardiovascular disease based on human pulse wave.Based on the analysis of the interference factor in the pulse wave, a new filtering method combined on Wavelet and Empirical Mode Decomposition was proposed; The Elastic Expansion Coefficient of Blood Vessel-ETK was extracted to as a parameter; by analyzing the human pulse wave in the time-frequency domain, distribution of wavelet entropy and wavelet entropy were extracted; the Statistic was applied to institute the hypotheses for these characteristic quantity for eliminating invalid features; The SVM models were adopted to classify the patients and healthy people supported by the clinical experiments with higher recognition accuracy. A human pulse wave detector was designed to acquire the pulse wave data, transfer the data wirelessly, filter the noise, extract the key parameter and recognize different pulse wave.This detector was applied to recognize healthy people and arteriosclerotic people accurately, which provided a new way for disease-diagnosing based on pulse wave.