Research On Analysis Of Pulse Signal And Recognition Of The Tradition Chinese Medicine Syndrome

The research of this thesis is a part of the research project"the embedded system of pulse signal analysis and processing". Traditional Chinese Medicine all along receives publicity for its unique diagnostic method and particularly curative effect. With the development of sensor and computer technology, people hope to apply modern technology to human pulse diagnosis to reveal the essence and features of pulse phenomena scientifically, which is the main research aspect in this paper.There have been a lot of reports about extracting features in time domain by analyzing the characteristics of human pulse. There are also a lot of works focused on how to use neural network to classify and recognize the pulse manifestations. But these techniques are far from perfect. In this paper, the following works are reported.Firstly, based on comparing different objective algorithms of human pulse manifestations considering that most traditional methods are apt to obtain the information only from time-domain and can not preserve all the original information of pulse, LPC, LPCC and MFCC are used as the new characteristics and Wavelet Transform (WT) is also adopted to acquire the new characteristics of pulse signal.Secondly, Vector quantization (VQ) technique is simple, effective and reliable. Especially, it can greatly decrease the computational load and memory. This technique obtains ideal results with high precision of recognition and rapid response rate. GMM technique has been well used in many processing aspects for statistical description of signal. By analyzing the pulse signal, the recognition systems based on VQ and GMM have been constructed. Using the system, four kinds of Traditional Chinese Medicine syndrome types have been successful recognized. By comparing the result, the system optimization is introduced for clinical experiment in future. Finally, the algorithms designed above are used in a system of pulse recognition. The experiment results show that the identification of Traditional Chinese Medicine syndrome types based on VQ model is effect,but not ideal. The relation between pulse features and syndrome types need more work time to find in the future.As the algorithm implemented in this paper is in accordance with characteristics acquisition and recognition of Traditional Chinese Medicine syndrome types, it could be used as reference in objective research and real clinics. It also has much significance to develop the study of Traditional Chinese Medicine.