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Differential entropy feature for EEG-based emotion classification
Abstract
EEG-based emotion recognition has been studied for a long time. In this paper, a new effective EEG feature named differential entropy is proposed to represent the characteristics associated with emotional states. Differential entropy (DE) and its combination on symmetrical electrodes (Differential asymmetry, DASM; and rational asymmetry, RASM) are compared with traditional frequency domain feature (energy spectrum, ES). The average classification accuracies using features DE, DASM, RASM, and ES on EEG data collected in our experiment are 84.22%, 80.96%, 83.28%, and 76.56%, respectively. This result indicates that DE is more suited for emotion recognition than traditional feature, ES. It is also confirmed that EEG signals on frequency band Gamma relates to emotional states more closely than other frequency bands. Feature smoothing method- linear dynamical system (LDS), and feature selection algorithm- minimal-redundancy-maximal-relevance (MRMR) algorithm also help to increase the accuracies and efficiencies of EEG-based emotion classifiers.
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Citations
Cites
Emotional state classification from EEG data using machine learning approach
Wang, X.-W., Nie, D., & Lu, B.-L. (2014) · Neurocomputing · doi:10.1016/j.neucom.2013.06.046 · Cited by 755
Self-citation
Cited by
EmotionMeter: A Multimodal Framework for Recognizing Human Emotions
Zheng, W.-L., Liu, W., Lu, Y., Lu, B.-L., & Cichocki, A. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2797176 · Cited by 1,276
Self-citationEmotions Recognition Using EEG Signals: A Survey
Alarcao, S. M., & Fonseca, M. J. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2714671 · Cited by 1,201
Spatial–Temporal Recurrent Neural Network for Emotion Recognition
Zhang, T., Zheng, W., Cui, Z., Zong, Y., & Li, Y. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2788081 · Cited by 595
Liu, W., Qiu, J.-L., Zheng, W.-L., & Lu, B.-L. (2022) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2021.3071170 · Cited by 452
Self-citationHoussein, E. H., Hammad, A., & Ali, A. A. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-07292-4 · Cited by 426
Metadata
- Authors
- Duan, R.-N., Zhu, J.-Y., & Lu, B.-L.
- Venue
- 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)
- Publisher
- IEEE
- Published
- 2013-11
- Pages
- 81-84
- ISSN
- 1948-3554 (ISSN-L)
- OpenAlex
- W1970727126
- Cited by
- 1,100
- References
- 1
- FWCI
- 10.90
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Duan, R.-N., Zhu, J.-Y., & Lu, B.-L. (2013). Differential entropy feature for EEG-based emotion classification. 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER). https://doi.org/10.1109/ner.2013.6695876
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