A Noninvasive Detection For Arterioselerosis Based On Pulse Wave Analysis

In the modern society, with the rapid development of the economy and the constant change of the lifestyle, environment and diet, the vascular disease (such as atherosclerosis) morbidity and mortality is on the increase. As a physiological signal of the body, the pulse signal reflects much information of the human cardiovascular according to its shape, strength and speed. So the study of the pulse signal is important for the early prevention of the atherosclerotic disease.First, the generation mechanism and the information contained of pulse wave is introduced, along with the analysis of the detection and processing methods of the pulse wave at home and abroad. Based on the feature of the signal, a pulse signal acquisition system is designed which is applied in the clinical use to collect the pulse data.Due to the noise contained in the collected pulse signal and the baseline drift, the wavelet threshold denoising and cubic spline interpolation are applied in this paper to suppress the baseline drift. Then, based on the previous research and clinical trial results, six features relevant to the atherosclerosis are selected, which cover the time and frequency domain and fully reflect the characteristics of the pulse waveform. For these features, the neural network is used for classification, which achieves a high accurate recognition rate and the pulse waves of people in good health and with atherosclerosis are well distinguished.After the single waveform analysis, pulse velocity is investigated in this paper, mainly focusing on the radial pulse velocity. In the pulse velocity analysis, the traditional peak-peak method is first applied, and the results of which indicate that the radial pulse wave velocities in different population show different values and possess some clinical meaning. Then the noise interference with the peak considered, a new method called generalized cross correlation method is proposed to calculate the pulse velocity. The results show that when the peak is contaminated by the interference, the new method achieves a better performance.Finally, a set of pulse signal detection system is developed in this paper, in which the pulse features recognition and the pulse velocity calculation method proposed are applied. The system is convenient for the users to observe their physical condition.