Conv1d and GRU-based EEG emotion recognition method

Guoxia Zou

doi:10.1117/12.2631432

18 March 2022 Conv1d and GRU-based EEG emotion recognition method

Guoxia Zou

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121681B (2022) https://doi.org/10.1117/12.2631432
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

Recognition and classification of emotion is an important research direction in emotion computing. At present, the research of the emotional recognition focus mainly on vision and voice, and the accuracy of the recognition and the classification is very low, which is not enough for commercial application. Therefore, in recent years, the electroencephalogram (EEG) emotion recognition research has become an important direction in the emotion computing. The EEG emotion is controlled by the central nervous system, it is not easy to be controlled by subjective consciousness, and can reflect the objective and the real emotion. Therefore, this paper proposes an EEG emotion classification model based on one-dimensional convolution neural network (conv1d) and a gated recurrent unit (GRU). In the experiments, this paper collected the EEG emotion signals with the open source brain-computer interfacing (OpenBCI). After collecting seven kinds of emotion data, the collected EEG signals are sorted into a training set and a test set. After data training, the accuracy of the emotion classification in the model can reach more than 90%. This model has high accuracy and simple data processing.

Citation Download Citation

Guoxia Zou "Conv1d and GRU-based EEG emotion recognition method", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121681B (18 March 2022); https://doi.org/10.1117/12.2631432

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