Models and methods for the study of cerebral circulation autoregulation

The work contains a review of modern methods and tools used to study the regulation of cerebral circulation. The first part discusses the basic concepts of the mathematical description of regulatory processes based on the biomedical signals analysis. Among them are the Fourier transform and transfer function, signal coherence, convolution of functions, correlation analysis, fractal analysis, wavelet transform, artificial neural networks, Hilbert-Huang transform. The second part presents works in which these methods are used for medical examinations. The analysis showed that there is serious competition between linear and non-linear models of the functioning of the cerebral blood flow autoregulation system. This suggests that there is currently no single approach to solving the problem, and there remains a need to continue the development of new methods and models and their implementation in medical practice. Key words: mathematical models, cerebral blood flow autoregulation, biomedical signals