Analysis Of Several Acupuncture Experimental Data

Acupuncture is a special method in the Chinese traditional treatment manipulations. It is very important for clinic diagnosis and research to explore the function of acupuncture and its mechanism. But, at present, the research on the acupuncture just emphasizes on the experiment and little on the electrical mechanism. With the development of the data analysis technology, it has made the mathmatics base for the study of the acupuncture manipulation quantifying. Wavelet is one of the modern time series analysis theories, which has an obvious advantage in analyzing the complex electro-neural signals. In this paper, the acupuncture experimental data is analyzed by many mathematic methods and then the characteristic of the signals is found out to provide the available condition for setting up the acupuncture experimental model.In this paper, firstly, the mechanism of the acupuncture experiment is introduced and then the experimental data is analyzed and the results are found out by means of single factor variance analysis and two factors variance analysis. Thirdly, new arithmetic named wavelet entropy is introduced, which is used to analyze the acupuncture manipulations. The results are found out by two ways—numerical value and time evolution figure: first, the Shannon wavelet entropy (SWE), which is made of Shannon theory and wavelet entropy, is applied to make the difference of four acupuncture manipulations in the numerical form; Secondly, making some change on the base of SWE, the wavelet energy entropy and wavelet time entropy are used to make the time evolution of four acupuncture manipulations and get the difference of them. Through the two analysis methods, the good results are got, and the result make a theory prepare for the next experiment.