Non-invasive Estimation Of Central Aortic Pulse Wave Based On Dual-channel Blind System Identification

Nowadays, pulse wave is very important in predicting and treatment of Cardiovascular System (CVS) diseases because it provides tremendous physiological and pathological information of human CVS. So far, blood pressure measured at brachial artery is used as a routine method in diagnosis of CVS diseases. However, comparing to brachial artery, Central Aortic Pulse wave (CAP) is generally more informative about cardiac dynamics and global circulation. In order to monitor CVS noninvasively and effectively, a new method based on dual-channel blind system identification was proposed in this thesis to reconstruct CAP from two channel noninvasive Peripheral Aortic Pulse waves (PAP) and to establish FIR black-box model and IIR gray-box model for cardiovascular system. The main work in the thesis is as follows:First, background, significance and relative achievements of former researches were introduced in the first chapter of the thesis. The thesis described the significance of CVS modeling and introduced the pathological and physiological significance of the CAP. Reviewed the current CAP estimation noninvasive methods and pointed out advantages and disadvantages of these methods. Based on the characteristics of the CVS, apply T-tube model to simulate the cardiovascular system, acquiring the brachial artery, femoral artery and central artery signals, provided a theoretical basis for blind identification algorithm.Second, the thesis introduced the dual-channel FIR blind identification algorithms, the maximum likelihood methods (including CR algorithm and TSML algorithm) and subspace algorithm. Besides, the thesis proposed the dual-channel IIR blind identification to better match the characteristics of the cardiovascular system and improve the estimation accuracy of central arterial pressure.Finally, after collecting the animal data for analysis and assessment of the proposed blind identification algorithm, the result showed that the TSML had a best precision. The TSML algorithm proposed in the thesis is simple, and has high clinical utility for future noninvasive monitoring of cardiovascular system.Besides, in order to study the internal mechanism of the cardiovascular system, this thesis also presents Hammerstein-Wiener nonlinear model to establish the relationship between central artery and radial artery. The result shows that the model can be more consistent with the characteristics of the cardiovascular system.