Study on Intelligent Classification Algorithms in Pulse Instruments
The pulse diagnosis detects the circulation status of Qi and blood in human body with the help of pulse so as to guide disease diagnosis and treatment,prediction of the disease and health care.However,the bottleneck problem in the development of pulse instruments is how to extract pulse information from weak pulse signals.This paper reviewed recent studies about used basic machine learning(ML)algorithms,neural network algorithms,and ensemble learning algorithms to build a pulse classification models,starting with issues such as the characteristics of pulse signals,classification of pulse conditions in traditional Chinese medicine,and the challenges they face.The purpose is to explore the feasibility and effectiveness of establishing models to classify pulse phases based on ML algorithms by comparing the performances of different ML algorithms and experimental protocols from the view point of the classification accuracy of different pulse phases,aims to provide a reference for the development of pulse instruments.
国家科技期刊平台
NSTL
万方数据
