EEG-based Emotion Word Recognition
- 10.2991/acaai-18.2018.28How to use a DOI?
- affective computing; Electroencephalogram(EEG); Emotion words recognition; Feature extraction; Classification; Event Related Potential(ERP)
Emotion recognition rapidly gains interest from research community, which gives computer the ability to recognize, understand, express, and adapt to human emotions to help computer more intelligent. Traditional emotion recognition modalities (e.g. face and voice) always could not identify the totally true emotion state. Recently, with the development of electroencephalogram (EEG) equipment, utilizing EEG signals to build emotion recognition system is more and more feasible and meaningful. In this paper, an abstract emotional words classification task is designed, which requires participants judge the emotion polarity (positive or negative) for given words. Based on EEG signals, a series of study is re-explored, including data collecting, feature extraction, feature selection, and classification model. Furthermore, the Event Related Potential (ERP) components and behavioral data analysis uncover some meaningful conclusion on emotion recognition.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Weiwei Dong AU - Panpan Wang AU - Yazhou Zhang AU - Tianshu Wang AU - Jiabin Niu AU - Shengnan Zhang PY - 2018/03 DA - 2018/03 TI - EEG-based Emotion Word Recognition BT - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018) PB - Atlantis Press SP - 121 EP - 124 SN - 1951-6851 UR - https://doi.org/10.2991/acaai-18.2018.28 DO - 10.2991/acaai-18.2018.28 ID - Dong2018/03 ER -