The Study Of Early Diagnosis Of Atherosclerosis Based On Human Pulse

Atherosclerosis is a serious cardiovascular disease. It's harmful to human health, so the early diagnosis of it is of great significance. Pulse signal contains rich cardiovascular system information .In this paper, we analysed the pulse signal with engineering method and obtained the early diagnosis method of atherosclerosis.Based on the existing model of two elastic chambers and elastic tube, we build the circuit model of the radial artery. We could simulate the pulse signal in different parameters. We found the differences and similarities among different pulse in the simulation results. By changing the parameters of this model, we could explain the reasonableness in the way of Chinese pulse diagnosis.In the clinical trials process, we used three pulse acquisition instrument to collect the pulse of patients and normal persons . With the healthy people as the control group, the paper analyzed patients'pulse from the time domain and frequency domain. We extracted the amplitude, time and others in the time domain and focused on the analysis between patients and healthy people.In the frequency domain analysis, we calculated the bi-spectral of pulse signal. From the bi-spectrum results, we analysed the difference between patients and healthy people and gave a preliminary explanation of this differences. We also analysed pulse signal with HHT method combined with sample entropy. In the results, we calculated the sample entropy of the first intrinsic mode function and the energy distribution. Then we found parameters with a significant difference between them .In the time and frequency domain analysis method, we found cun, guan and chi pulse has no obvious difference, so we could just analysis one pulse of cun, guan and chi .In this paper we established radial artery circuit model and proved the way of pulse diagnosis in traditional Chinese medicine reasonable. Based on human pulse, we proposed a new idea about non-invasive detection of atherosclerosis.