Electrical Engineering Department, Bahria University, Karachi 75260, Pakistan.
Computer Science Department, Bahria University, Karachi 75260, Pakistan.
Sensors (Basel). 2019 Jan 26;19(3):522. doi: 10.3390/s19030522.
Most electroencephalography (EEG) based emotion recognition systems make use of videos and images as stimuli. Few used sounds, and even fewer studies were found involving self-induced emotions. Furthermore, most of the studies rely on single stimuli to evoke emotions. The question of "whether different stimuli for same emotion elicitation generate any subject-independent correlations" remains unanswered. This paper introduces a dual modality based emotion elicitation paradigm to investigate if emotions can be classified induced with different stimuli. A method has been proposed based on common spatial pattern (CSP) and linear discriminant analysis (LDA) to analyze human brain signals for fear emotions evoked with two different stimuli. Self-induced emotional imagery is one of the considered stimuli, while audio/video clips are used as the other stimuli. The method extracts features from the CSP algorithm and LDA performs classification. To investigate associated EEG correlations, a spectral analysis was performed. To further improve the performance, CSP was compared with other regularized techniques. Critical EEG channels are identified based on spatial filter weights. To the best of our knowledge, our work provides the first contribution for the assessment of EEG correlations in the case of self versus video induced emotions captured with a commercial grade EEG device.
大多数基于脑电图 (EEG) 的情绪识别系统都使用视频和图像作为刺激。很少有使用声音的，甚至更少的研究涉及到自我诱导的情绪。此外，大多数研究都依赖于单一的刺激来唤起情绪。“对于相同的情绪诱发，不同的刺激是否会产生任何与主体无关的相关性”这一问题仍未得到解答。本文介绍了一种基于双模态的情绪诱发范式，以研究是否可以用不同的刺激来分类诱发的情绪。提出了一种基于共同空间模式 (CSP) 和线性判别分析 (LDA) 的方法，用于分析由两种不同刺激诱发的恐惧情绪的人脑信号。自我诱导的情绪意象是考虑的刺激之一，而音频/视频剪辑用作另一种刺激。该方法从 CSP 算法中提取特征，然后 LDA 进行分类。为了研究相关的 EEG 相关性，进行了频谱分析。为了进一步提高性能，将 CSP 与其他正则化技术进行了比较。基于空间滤波器权重确定关键 EEG 通道。据我们所知，我们的工作首次评估了使用商用级 EEG 设备捕获的自我与视频诱发情绪的 EEG 相关性。
