Author(s)

Shaohua Wang¹, Jianli Jiang², Xiaobing Lu³

¹The Second People’s Hospital of Yichang, Yichang, China.
²The First People’s Hospital of Yichang, Yichang, China.
³The Institute of Mechanics, Chinese Academy of Sciences, Beijing, China.

The objectification of the pulse signal analysis is a practical problem. The classification of the pulse signal is studied based on the BP neural network. It is first analyzed how to select the characteristic factors of the pulse signal. Then the method of nondimensionalization/normalization on the pulse signal is presented to preprocess the characteristic factors. The classification of the pulse signal and the effects of the selection of characteristic factors are studied by using the normalized data and BP neural network. It is shown that nondimensionalization/normalization of the data is in favor of the training and forecasting of the network. The selection of characteristic factors affects the accuracy of forecasting obviously. The results of forecasting by selection of 8, 6 and 4 factors respectively show that the less the factors are, the worse the effects are.

BP Neural Network, Pulse Signal, Classification, Dimensional Analysis

Wang, S. , Jiang, J. and Lu, X. (2020) Study on the Classification of Pulse Signal Based on the BP Neural Network. Journal of Biosciences and Medicines, 8, 104-112. doi: 10.4236/jbm.2020.85010.