EEG emotion recognition technology for children with autism

Shengjie Zhang; Guanglu Liu; Rongkai Pan

doi:10.1117/12.2684370

1 August 2023 EEG emotion recognition technology for children with autism

Shengjie Zhang, Guanglu Liu, Rongkai Pan

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127543E (2023) https://doi.org/10.1117/12.2684370
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

Emotion recognition in children with autism has been a hot topic of research at home and abroad, and research on emotion recognition through facial features has made corresponding progress, but the observation of facial features is somewhat subjective and less objective. The EEG signal was reconstructed by wavelet packet decomposition to remove noise and artifacts. After that, the frequency band energy of the four rhythmic waves was extracted as features, and the SVM model optimized by genetic algorithm and the unoptimized SVM model were subjected to control experiments. The average accuracy of the parameter-optimized model was 80.37%, which was higher than that of the control group at 64.12%, and the accuracy rate was improved to a certain extent, which can provide an effective and objective basis for the diagnosis of autistic children.

Citation Download Citation

Shengjie Zhang, Guanglu Liu, and Rongkai Pan "EEG emotion recognition technology for children with autism", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127543E (1 August 2023); https://doi.org/10.1117/12.2684370

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