实用心电学杂志2024，Vol.33Issue(5)：491-498,8.DOI:10.13308/j.issn.2095-9354.2024.05.012
基于IKPCA-GA-BP算法的心电情绪识别研究
Study on ECG emotion recognition based on IKPCA-GA-BP algorithm
摘要
Abstract
Objective To improve the accuracy and efficiency of emotion recognition by using characteristic parameters of ECG signals,a genetic algorithm called improved kernel principal component analysis-genetic algorithm-back propagation(IKPCA-GA-BP)neural network based on improved kernel principal component analysis is proposed.Methods First,taking the data recorded by ECG sensors as test samples,the improved kernel principal component analysis algorithm with adaptive selection of γ values was used to perform data dimension reduction and data reconstruction on multiple groups of features,which had been extracted by the binary spline wavelet transform,to obtain comprehensive variables.Secondly,the back propagation neural network model was established,and the genetic algorithm was used to optimize the initial weights and bias values of the network.Finally,by changing the proportion of model training samples to test samples,the effects of emotion classification separately based on IKPCA-GA-BP algorithm and traditional recognition algorithm were comparatively analyzed.Results By this algorithm,related emotions could be recognized in about 1 s on the premise of an ensured accuracy rate of 96％.In addition,most models did not perform well in identifying sadness emotion,however,IKPCA-GA-BP algorithm obtained an accuracy rate of nearly 100％.Conclusion In ECG signals,P-wave,QRS complex and T-wave contain a lot of information that is helpful for emotion recognition(for example,R-R interval,P-wave amplitude,etc.).However,this information can not be directly used for experimental analysis,and requires effective combination and processing to maximize its efficacy.Furthermore,among four emotions:happiness,relaxation,sadness and fear,accurate recognition of sadness often challenges most recognition algorithms.关键词
心电信号/自适应选取γ值/核主成分分析/小波变换/情绪识别Key words
ECG signal/adaptive selection of γ value/kernel principal component analysis/wavelet transform/emotion recognition分类
医药卫生引用本文复制引用
吴启越,袁银龙..基于IKPCA-GA-BP算法的心电情绪识别研究[J].实用心电学杂志,2024,33(5):491-498,8.基金项目
江苏省高校自然科学基金资助项目(20KJB520008) （20KJB520008）
