Title :
Analysis of eight volume pulse elements based on the BP neural network
Author :
Kuixing Zhang ; Bozheng Zhang ; Rongfang Qu
Author_Institution :
Coll. of Sci. & Eng., Shandong Univ. of Traditional Chinese Med., Jinan, China
Abstract :
To solve the problem of the low rate of recognition in current complex pulse recognition, this paper puts forward a new approach to it. The paper preprocess and analyze the pulse information by using the neural network and genetic algorithm. The algorithm system includes pulse information collecting, network training, simulant diagnosis, correlation analysis. Pearson´s coefficient test shows the system is of high reliability and testing accuracy. This system is more effective to solve the problem of pulse elements recognition. The method that making collection analysis between waveform and finger sense factor will be helpful for further research on the formation mechanism.
Keywords :
backpropagation; cardiology; feature extraction; genetic algorithms; medical signal detection; neural nets; signal detection; BP neural network; Pearson coefficient test; complex pulse recognition; correlation analysis; finger sense factor; genetic algorithm; low-recognition rate problem; network training; pulse information analysis; pulse information collection; pulse information preprocessing; reliability accuracy; simulant diagnosis; testing accuracy; volume pulse element analysis; waveforms; Accuracy; Correlation; Fingers; Genetic algorithms; Interference; Neural networks; Testing;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2015 Seventh International Conference on
Conference_Location :
Wuyi
Print_ISBN :
978-1-4799-7257-9
DOI :
10.1109/ICACI.2015.7184790