Journal of Shandong University(Engineering Science) ›› 2020, Vol. 50 ›› Issue (4): 35-39.doi: 10.6040/j.issn.1672-3961.0.2019.679

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Emotional EEG recognition based on Bi-LSTM

LIU Shuai1,2, WANG Lei1,2*, DING Xutao1,2   

  1. 1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China;
    2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, China
  • Published:2020-08-13

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Abstract: To solved a challenging task of emotional electroencephalogram(EEG)recognition, this study proposed a bidirectional long short-term memory(Bi-LSTM)EEG classification model and explored the emotional mechanism of the brain, with the highest arousal accuracy of 76.78% and the highest valence accuracy of 77.28%. The Bi-LSTM model, compared with other models, had excellent performances in the recognition of emotional EEG. The Bi-LSTM model was used to explore the brain emotion mechanism by comparing the accuracy of different frequency bands, brain regions and feature density, and the results showed that the frequency bands, brain regions and feature density with the highest emotional correlation in the brain were respectively the α and β regions, Parietal Lobe and Frontal Lobe, 50 and 15.

Key words: EEG emotional recognition, deep learning, emotion, EEG, Bi-LSTM

CLC Number: 

  • TP183
[1] 乔建中. 情绪研究: 理论与方法[M]. 南京:南京师范大学出版社, 2003:1-10.
[2] YANG X, LIU J, CHEN Z, et al. Semi-supervised learning of dialogue acts using sentence similarity based on word embeddings[C] // International Conference on Audio. Shanghai, China:IEEE, 2015:882-886.
[3] ADEYANJU I A, OMIDIORA E O, OYEDOKUN O F. Performance evaluation of different support vector machine kernels for face emotion recognition[C] //SAI Intelligent Systems Conference 2015. London, UK:IEEE, 2015:804-806.
[4] 聂聃, 段若男. 基于脑电的情绪识别研究综述[J]. 中国生物医学工程学报, 2012, 31(4):595-606. NIE Dan, DUAN Ruonan. A survey on EEG based emotion recognition[J].Chinese Journal of Biomedical Engineering, 2012, 31(4):595-606.
[5] QIAO R, QING C, ZHANG T, et al. A novel deep-learning based framework for multi-subject emotion recognition[C] //International Conference on Information. Dalian, China:IEEE, 2017:181-185.
[6] 阚威, 李云. 基于LSTM的脑电情绪识别模型[J]. 南京大学学报(自然科学), 2019, 55(1):116-122. KAN Wei, LI Yun. Emotion recognition from EEG signals by using LSTM recurrent neural networks[J]. Journal of Nanjing University(Natural Sciences), 2019, 55(1):116-122.
[7] SONG T, ZHENG W, SONG P, et al. EEG emotion recognition using dynamical graph convolutional neural networks[J]. IEEE Transactions on Affective Computing, 2018(99):1-10.
[8] LI X, SONG D, ZHANG P, et al. Emotion recognition from multi-channel EEG data through convolutional recurrent neural network[C] //2016 IEEE International Conference on Bioinformatics and Biomedicine(BIBM). Shenzhen, China:IEEE, 2016:352-359.
[9] (¨overO)ZAL YILDIRIM. A novel wavelet sequences based on deep bidirectional LSTM network model for ECG signal classification[J]. Computers in Biology & Medicine, 2018, 96(1):189-202.
[10] ADAM K, SMAGULOVA K, JAMES A P. Memristive LSTM network hardware architecture for time-series predictive modeling problem[C] //2018 IEEE Asia Pacific Conference on Circuits and Systems(APCCAS). Chengdu, China:IEEE, 2018:459-462.
[11] KOELSTRA S, MUHL C, SOLEYMANI M, et al. DEAP: a database for emotion analysis using physiological signals[J]. IEEE Transactions on Affective Computing, 2012, 3(1):18-31.
[12] MURRAY I R, ARNOTT J L. Toward the simulation of emotion in synthetic speech: a review of the literature on human vocal emotion[J]. The Journal of the Acoustical Society of America, 1993, 93(2):1097-1108.
[13] KONG W, DONG Z Y, JIA Y, et al. Short-Term residential load forecasting based on LSTM recurrent neural network[J]. IEEE Transactions on Smart Grid, 2018(10):841-851.
[14] HOW D N T, SAHARI K S M, HU Y, et al. Multiple sequence behavior recognition on humanoid robot using long short-term memory(LSTM)[C] //IEEE International Symposium on Robotics & Manufacturing Automation. Kuala Lumpur, Malaysia: IEEE, 2014: 109-114.
[15] XIAO R, CUI X, ZHOU P, et al. LSTM based on the classification of emotion about user evaluation on shopping site[C] //2016 International Conference on Identification, Information and Knowledge in the Internet of Things(IIKI). Beijing, China:IEEE, 2016:52-53.
[16] DAIMI S N, SAHA G. Classification of emotions induced by music videos and correlation with participants, rating[J]. Expert Systems with Applications, 2014, 41(13): 6057-6065.
[17] MERT A, AKAN A. Emotion recognition from EEG signals by using multivariate empirical mode decomposition[J]. Pattern Analysis and Applications, 2016, 21(1):81-89.
[18] GUPTA R, LAGHARI K U R, FALK T H. Relevance vector classifier decision fusion and EEG graph-theoretic features for automatic affective state characterization[J]. Neurocomputing, 2016, 174(2):875-884.
[19] ATKINSON J, CAMPOS D. Improving BCI-based emotion recognition by combining EEG feature selection and kernel classifiers[J]. Expert Systems with Applications, 2016, 47(1):35-41.
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