摘要
情绪识别是指通过人的面部表情、行为动作或者生理信号等信息识别人的情绪状态,其成果在医疗辅助、教育、交通安全等方面有很大的应用价值。由于脑电信号的客观真实性等特点,使用脑电信号进行情绪识别研究受到国内外学者们的广泛关注。查阅了大量脑电情绪识别相关文献并进行归纳、分析和总结。首先,对情绪以及情绪识别的定义、情绪的分类模型、脑电信号的采集和预处理等理论知识进行了详细的解释和分析,给出了脑电情绪识别的一般框架。其次,从时域特征、频域特征、时频特征和非线性特征四方面综述了用于情绪识别的各类脑电特征的提取方法,介绍了脑功能网络的构建以及脑网络属性的提取方法,分析了每类特征和方法的优缺点。然后,对脑电情绪识别中常用的分类算法的特点、优缺点以及适用场景进行了分析。最后,对该领域目前的难点和未来的发展方向进行了总结和展望。可以帮助研究人员系统地了解基于脑电信号的情绪识别研究现状,为后续开展相关研究提供思路。
Emotion recognition refers to the recognition of a person’s emotional state through information such as facial expressions, behavioral actions or physiological signals, and its results have great application value in medical assistance, education, traffic safety and other areas. Due to the objective and realistic characteristics of EEG signals,the research on emotion recognition using EEG signals has received a lot of attention from scholars at home and abroad. A large amount of literature related to EEG emotion recognition has been reviewed, analyzed and summarized. Firstly, the theoretical knowledge of emotions and the definition of emotion recognition, the classification model of emotions, the acquisition and pre-processing of EEG signals are explained and analyzed in detail, and a general framework of EEG emotion recognition is given. Secondly, the extraction methods of various types of EEG features used for emotion recognition are reviewed from four aspects: time domain features, frequency domain features,time-frequency features and non-linear features. The construction of brain functional networks and the extraction methods of brain network attributes are introduced, and the advantages and disadvantages of each type of features and methods are analyzed. Then, the characteristics, advantages and disadvantages as well as the applicable scenarios of the commonly used classification algorithms in EEG emotion recognition are analyzed. Finally, the current difficulties and future directions of the field are summarized and outlined. It can help researchers to systematically understand the current status of research on EEG signal-based emotion recognition and provide ideas for the subsequent development of related research.
作者
王忠民
赵玉鹏
郑镕林
贺炎
张嘉雯
刘洋
WANG Zhongmin;ZHAO Yupeng;ZHENG Ronglin;HE Yan;ZHANG Jiawen;LIU Yang(School of Computer Science and Technology,Xi'an University of Posts and Telecommunications,Xi'an 710121,China;Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing,Xi'an 710121,China;Xi'an Key Laboratory of Big Data and Intelligent Computing,Xi'an 710121,China)
出处
《计算机科学与探索》
CSCD
北大核心
2022年第4期760-774,共15页
Journal of Frontiers of Computer Science and Technology
基金
国家自然科学基金(61373116)
陕西省教育厅项目(18JK0697)。
关键词
情绪识别
脑电信号
特征提取
情绪分类
脑网络
emotion recognition
EEG signals
feature extraction
emotion classification
brain network
