BRAIN - COMPUTER INTERFACE FOR COMMUNICATION AND ESTIMATION OF HUMAN EMOTION FROM EEG AND VIDEO

S. Radeva, D. Radev
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Abstract

The brain-computer interface (BCI) aim to use Electroencephalography (EEG) or other measures of brain functions can be implemented for communication with smart devices for disabled persons. For connection with different smart devices was used recorded with experimental setup electrophysiological signals for execution of five different mental tasks. The recorded brain signals were processed for their transformation into commands to different devices. This signal processing aims to extract some specific features of brain signals and transform them into algorithms for connection with smart devices. Processed signals after noise filtering, clustering and classification with Bayesian Network classifier and pair-wise classifier was estimated and put into brain-computer interface for connection with smart devices. Recent advances in emotion recognition use a combination of two intrapersonal modalities face and EEG to estimate emotion. In this research is made an attempt to combine received results on the base of record electrophysiological signals at execution of five different mental tasks with estimation of human emotion. This will help to provide a framework for reliable EEG emotional state estimation combined with facial emotion analysis in developed task-oriented BCI.
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脑机接口,用于从脑电图和视频中交流和估计人类情感
脑机接口(BCI)旨在利用脑电图(EEG)或其他脑功能测量方法,实现与残疾人智能设备的通信。为了与不同的智能设备连接,使用实验装置记录执行五种不同心理任务的电生理信号。记录下来的大脑信号经过处理,转化为对不同设备的指令。这种信号处理的目的是提取大脑信号的某些特定特征,并将其转化为与智能设备连接的算法。处理后的信号经过噪声滤波、贝叶斯网络分类器和成对分类器的聚类和分类后进行估计,输入脑机接口与智能设备连接。情绪识别的最新进展是将人脸和脑电图两种个人模式相结合来估计情绪。在本研究中,我们尝试将基于记录的五种不同心理任务的电生理信号所得到的结果与对人类情绪的估计相结合。这将为成熟的任务型脑机接口中结合面部情绪分析的可靠脑电情绪状态估计提供一个框架。
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