生物医学工程研究2024，Vol.43Issue(1)：33-39,7.DOI:10.19529/j.cnki.1672-6278.2024.01.05
基于心电信号图像特征及卷积神经网络的情绪识别研究
Research on emotion recognition based on image features of ECG signal and convolutional neural network
摘要
Abstract
In order to improve the accuracy of emotion recognition,we used convolutional neural network and transfer learning method to propose an emotion recognition method based on electrocardiography(ECG)signal image features.First,the ECG signal was preprocessed to remove noise,and then the time-domain waveform and time-frequency graph of the ECG signal were extracted.Final-ly,transfer learning and the time-domain and frequency-domain features contained in the dual input EfficientNetV2 network learning images were used and classified to obtain the corresponding emotion categories.The results of validation on the public dataset Amigos showed that the recognition accuracy of arousal,titer and dominance were 91.63%,95.27%and 92.32%,respectively.Compared to other emotion recognition methods,this method has higher accuracy.关键词
情绪识别/心电信号/特征提取/双输入/卷积神经网络Key words
Emotion recognition/Electrocardiography/Feature extraction/Dual input/Convolutional neural network分类
医药卫生引用本文复制引用
李永康,方安成,陈娅南,谢子奇,潘帆,何培宇..基于心电信号图像特征及卷积神经网络的情绪识别研究[J].生物医学工程研究,2024,43(1):33-39,7.基金项目
四川省自然科学基金(2022NSFSC0799). （2022NSFSC0799）
