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Sensors 2018, 18(3), 841; https://doi.org/10.3390/s18030841

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

1
China National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450002, China
2
Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Received: 9 February 2018 / Revised: 4 March 2018 / Accepted: 7 March 2018 / Published: 12 March 2018
(This article belongs to the Special Issue Advanced Physiological Sensing)
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Abstract

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. View Full-Text
Keywords: self-induced emotion recognition; electroencephalogram (EEG); features; electrodes; neural patterns self-induced emotion recognition; electroencephalogram (EEG); features; electrodes; neural patterns
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Zhuang, N.; Zeng, Y.; Yang, K.; Zhang, C.; Tong, L.; Yan, B. Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals. Sensors 2018, 18, 841.

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