Research On Physiology Signals In Cardiovascular Risk Assessment System

In21st century, people’s living standards and quality of life have improvedsignificantly. However, due to the rapid aging of the population coupled with people improperlifestyle, inappropriate diet and lack of physical exercise and other reasons, a lot of middleand old is likely to suffer from coronary heart disease,high blood pressure, heart disease andother cardiovascular diseases. They have been a serious threat to human health. Therefore,how to be able to quickly detect the vascular system of early cardiovascular morbidity andrelated abnormal autonomic function,how to established the effective model to determine andassess the occurrence and development of cardiovascular disease, and how to earlyintervention measures to establish a real-time monitoring and evaluation system aresignificant. Currently physiological signal and its variants, which reflect the state of thenervous system and the cardiovascular status of research has become a hot spot.This paper studies from ECG signals and pulse wave signal,which carry a amounts ofinformations. These signals can not only reflect cardiovascular status but also they are the riskfactors of cardiovascular risk evaluation system.Firstly, we use traditional median filtering method and maxima method、 composeand reconstruction signals and detection the feature points of ECG and pulse wave signal.Compared to traditional methods, we use wavelet transform to decomposite and reconstructthe signals.Then,we use improved threshold modulus maxima method to extract feature pointsof ECG and pulse wave signals.. Focus on Hilbert-Huang method.We use empirical modedecomposition to filter ECG and pulse wave signal, according to stratified results, analysis theinstantaneous frequency and precisely determine its frequency characteristic feature points.Then focus on how to extract the pulse transit time (PTT), it is extracted by featurepoints of ECG and pulse wave signal. The variability of the PTT signal combined heart rate variability (HRV) conduct a joint analysis. Because physiological signal variability analysisespecially HRV have been more mature and been developed a variety of methods,.Theresearch of HRV may reflect the cardiovascular system status and regulatory function of thenervous system,and HRV can reflect the physiological mechanisms of cardiovascularpathology analysis. So we use correlation analysis to study the transit time variability andheart rate variability in the timing sequence and frequency.Then,using statistical formulas andmodels methods for correlation analysis. Hope to be able to tap the pulse transit timevariability of the pathological mechanisms.Finally, we design cold pressor test using Finapress and Polo Smith to test and verifythe relevant statistical results.We make a preliminary assessment and provide a theoreticalbasis for early warning model.