Study On Evaluation For Autoregulation Ability Of Cerebral Blood Flow

Cerebral autoregulation is defined as a mechanism that maintains cerebral blood flow at a relatively constant level despite changes of cerebral arteral blood pressure over a wide range. Impaired autoregulation,which may lead to ischemia and hyperaemia in the brain, is associated with pathophysiological conditions including intracranial tumours, head injury, stroke, hypertension in the brain. Therefore, assessing and monitoring cerebral autoregulation is important to guide the treatments of patients suffering from such conditions. Although great efforts have been made to develop methods for assessing the autoregulation using mathematical models and signal processing techniques, the assessment of autoregulation still suffers from large variability which is not yet fully understood. In addition, there is currently no accepted standard for assessing cerebral autoregulation for clinical applications.In this thesis, methods for assessing cerebral autoregulation are investigated and evaluated using linear modelling approaches, showing that the phase difference between cerebral blood flow velocity and blood pressure is a reliable indicator of the autoregulation. By the use of real-time, fast time-varying system identification methods to research on tracking brain's autoregulation function of blood flow, which can provide quantitative basis for the treatment of cerebral vascular disease.At the same time, the Cross-approximate entropy of nonlinear dynamics is used to study autoregulation ability of cerebral blood flow in this thesis. The experimental results revealed that the method can achieve real-time, continuous quantitative assessment autoregulation capacity of cerebral blood flow, and provided a nice method to evaluate the compensatory capacity of circulatory system and brain diseases.