A Detecting And Analyzing System For Ultrasound Doppler Blood Flow Signals In Human Common Carotid Arteries

Cerebrovascular disease is one of the common illnesses harmful to human health. Stroke in particular, with characteristics of high morbidity, high mortality and high rate of relapse, brings not only physical pain to the patients but also a heavy load to the family and the society. Studies have shown that cerebral vascular hemodynamic parameters and signal spectrum feature parameters of blood flow are critical factors for early diagnosis of cerebrovascular disease. The common carotid artery, which is the main organ for supplying blood to the cerebral circulation, usually acts as the most important window for detecting and analyzing these two kinds of parameters, because the cerebral blood vessels covered by the stiff skull is difficult to detect.The analyzers for cerebral vascular hemodynamic parameters, which are widely used in the market generally take common carotid artery blood flow signal as cyclic stationary signal, with the disadvantages of complex structure, large size, complicated operation process and expensive price and so on. Therefore, in this thesis a detecting and analyzing system for ultrasound Doppler blood flow signals in human common carotid arteries is proposed which is practical, simple and potable for analysis of non-stationary, non-linear, non-strict cyclic blood flow signals. The system includes two parts, the hardware system is a device of ultrasonic blood flow detection and the software system is for data acquisition and analysis.Taking the results of Aloka color Doppler ultrasonic detection system as standard reference data, the hemodynamic and spectral characteristics parameters are calculated based on the blood flow velocity waveform collected by the two instruments to verify the accuracy of the system by comparison. After collecting the data of common carotid artery flow velocity measured by the two instruments, and using brachial artery blood pressure, hemodynamic parameters including pulsatility index, dynamic resistance and peripheral resistance are calculated. Further, wavelet transform is adopted for time-frequency analysis of velocity waveform, which can be extracted to six characteristic peaks, respectively corresponding to the activities of cardiac, respiratory, myogenic, neural, endothelial cells which are effected by NO and non-NO factors. The comparative studies show that the hemodynamic parameters of the two instruments have no significant difference, and the comparable peak frequencies are almost the same. Therefore, the design of the detecting and analyzing system for ultrasound Doppler blood flow signals in human common carotid arteries proposed in this thesis has certain accuracy to provide effective blood flow information, and would be applied to the early diagnosis and prevention of cerebrovascular disease in the future.