Research Of Noninvasive Cardiac Output Monitoring Based On Photoplethysmography

Cardiovascular disease (CVD) is the leading cause of mortality in the world, such as myocardial infarction, hypertension, and stroke. Hence, the early detection and diagnosis is vital for effective prevention and therapy of disease, and it may play an important role on human health. Blood pressure, heart rate, cardiac output and arterial stiffness are all important cardiovascular parameters and the index for diagnosis, because they contain abundant physiological information.Invasive and non-invasive methods are usually used in the monitoring of cardiovascular parameters currently. Both of them have their advantages and disadvantages. The invasive methods are usually used in surgery with its high accuracy, but its high cost, complex operation and easy to lead mortality will limit its use. The non-invasive ways are convenient and cost low, but their stability and accuracy do not match the invasive methods'. So the non-invasive ways are more suitable for the assistant diagnose and the homecare.The target of this research is to estimate the cardiovascular parameters based on non-invasive photoplethysmography signal and then evaluate cardiovascular system condition. This method can also be used at home and other sites exclude hospitals because of its convenient operation, low cost, and stable performance. So it can help early detection, early diagnosis, early treatment for cardiovascular disease. In conclusion, this research has very important real and science value.There are two parts in this thesis including experiment and data analysis, and the result can verify the feasibility and validity of noninvasive monitoring cardiac output with photoplethysmography. Theoretically, we introduce principles of Windkessel model and auto-regressive moving average model parameters estimation, and we can derive the cardiac output operator according to them. Experimentally, we design proposal and measure the raw PPG data under the protocol, then we process the data with above mentioned theory. Finally, we discuss the relationship between the estimated cardiac output and the reference cardiac output, and we evaluate the algorithm accuracy and put forward the improved method. The result us shows that the estimated cardiac output can indicate the subject's real health condition and his/her physiological status and it has good relevance with Impedance method's output, so we can validate the feasibility and validity of algorithm used in this thesis.