情绪相关EEG和ERP信号的识别与分析:基于心理学的视角

Yang Yuankui, Z. Jianzhong
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引用次数: 13

摘要

脑电图(EEG)在心理学领域被广泛用于记录人脑活动。随着技术的发展,情绪处理功能区的神经基础逐渐被揭示出来。为了从脑电信号和噪声的背景中提取有用的情绪信息,我们提出将心理学方法与模式识别等信号处理技术相结合。本文首先回顾了情绪研究领域的心理学方法和信号处理技术,并指出了这两种方法的联系。其次,介绍了一种客观评价情绪能力的方法,该方法包括分析脑电信号的频率波动和额叶脑电信号的不对称性。然后,我们以事件相关电位(ERP)在人脸识别任务和悲伤/快乐/中性面部表情识别任务中的应用为例进行了研究。最后,指出了该研究领域目前存在的困难,并提出了解决这些问题的可能方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition and analyses of EEG & ERP signals related to emotion: from the perspective of psychology
Electroencephalography (EEG) is widely used to record activities of human brain in the area of psychology for many years. With the development of technology, neural basis of functional areas of emotion processing is revealed gradually. In order to extract the useful information of emotion from the background of EEG signals and noise, we propose to combine methods of psychology and the technology of signal processing such as pattern recognition, etc. In this paper, we first review the psychological methods and signal processing technology in the field of emotion research, and point out the junctions of these two approaches. Secondly, we introduce a method to evaluate emotion competence objectively, which involves the analyses of frequency fluctuations of EEG signals and frontal EEG asymmetry. Then, we take an example of event-related potentials (ERP) study about the face recognition task and the discrimination of sad/happy/neutral emotional facial expressions task. Finally, we indicate the present difficulties in this research area, and advance the possible solution to resolve these problems.
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