Analysis of acupoint bioelectricity based on wavelet entropy

Combing modern science and technology with traditional Chinese medicine theory, a new analysis method was used to discover the peculiarity of the acupoint in this paper. Based on wavelet analysis theory, the method adopted the concept of wavelet entropy. During experiments, four adjacent non-acupoints around each acupoint were chosen as a control group. The electrophysiological signals collected from ten acupoints were analyzed to see whether there existed differences between acupoints and non-acupoints. The five layer wavelet decomposition was carried out on the electrophysiological signals of acupoints. Results showed that acupoints electrophysiological signals acquired from healthy person have higher wavelet entropy (WE) than nearby non-acupoint area. The analysis results of healthy individuals also reflected that the acupoints’ electrical signal sequence had a higher degree of disorder and were more complex than normal electrophysiological signal. However, when comparing KI 9 acupoint of patients with kidney disease with the corresponding non-acupoint, no clear distinction was obtained between their WE values. Thus, the results demonstrated that this method was capable of identifying the differences between acupoint and non-acupoint. The larger WE value of meridians electrophysiological signals indicated that the internal organ related to the acupoint potentially could transfer more complicated electrophysiological information through the meridian system. The kidney disease patients may have weakened information transfering and expressing ability on KI 9 acupoint. The phenomenon found in this article could provid a new viewpoint for the clinical application of acupuncture and may have great significance to the study of traditional Chinese medicine.