Issues On The Applications Of Chaos In The Hemodynamics

Chaos is a subject rapidly developed in the past twenty years, which is in close relation with some other subjects. It has been extensively applied whether in the field of mathematics, physics, life science, informatics or in the field of economics, geoscience, astronomy, etc. The analysis and applications of chaos have become a hot topic in many disciplines.In this dissertation, chaotic theory has been simply introduced, the methods of chaotic characteristic analysis and chaos control have been reviewed, the applications of chaos in the biomedicine have been summarized systemically, a noise reduction method is presented for the chaotic signal containing noise by the wavelet packet analysis, and the following research results have been obtained:(1) A digital system was designed. It can get the frequency spectrum image of Doppler Ultrasound's activities. Through the analysis and research on the printer's output data format, the frequency spectrum image is stored in the familiar image format. With the image manipulation technique, the time series data of the blood flow activity can be obtained, which are fit for various nonlinear analyses. Based on this system, the original blood flow activity can be observed, and the changes of the data in the experiments can also be detected timely. It is proved by actual examples that this system is feasible, and the obtained time series data of the blood flow activity are exact. It can offer assistance for the further study on the cardiovascular and cerebrovascular disease. It can also provide the foundation for uniting nonlinear science and ultrasonic diagnosis in medicine.(2) Numerically evaluate the value of the largest Lyapunov exponent on diagnosing the various stenosis degrees of internal carotid arteries in white rabbits and in order to diagnose the angiostenosis with transcranial Doppler ultrasound (TCD).(3) It is presented that correlation dimension of the chaotic signal can be computed by the nonlinear time series of the wavelet packet transform modulus instead of the chaotic signal itself. Based on simulation testing and noise analysis with some examples, it is found that this method is accurate and credible. It can also get over the signal disturbance caused by the noise during the sampling. When it is applied to the hemodynamics, some valuable results can be obtained.