脑电情绪识别研究现状及展望

Research of Current Status and Future Outlook of EEG Emotion Recognition

脑电的研究正在不断突破并取得成果,在情绪识别领域,包含脑电信号采集、数据预处理、提取时频特征、构建脑网络特征和分类识别等步骤。本文综述了脑电特征计算方法的现状,脑电情绪识别的步骤、方法,归纳总结了应用方式并对今后的发展进行展望。脑电情绪识别的应用展现出巨大的潜力,如心理健康评估、情绪感知计算和人机交互。随着机器学习和人工智能的进步,以及脑电图信号处理的改进,有望进一步提高基于脑电图的情绪识别的准确性和可靠性。本文对脑电情绪识别特征计算方法,情绪识别的步骤和临床应用方面的具体事例进行了阐述,并对未来的方向进行了展望,对于研究人员系统地了解脑电情绪识别具有积极意义。

The research on electroencephalography(EEG)is continuously making progress.In the field of emotion recognition,it involves steps such as EEG signal acquisition,data preprocessing,time-frequency feature extraction,the construction of brain network features,and classification recognition.This paper reviewed the current status of EEG feature calculation methods,steps and methods of EEG emotion recognition and summarizes their application and future development.EEG emotion recognition shows great potential in applications such as psychological health assessment,emotion perception computing,and human-computer interaction.With the progress of machine learning and artificial intelligence,as well as the improvement of EEG signal processing,it is expected to further enhance the accuracy and reliability of EEG-based emotion recognition.In this paper,the calculation method of EEG emotion recognition features,the steps of emotion recognition,and the specific cases of clinical application are described,and the future direction is projected,which has positive significance for researchers to systematically understand EEG emotion recognition.