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AuthorCheng, Wen Xin
AuthorGao, Ruobin
AuthorSuganthan, P. N.
AuthorYuen, Kum Fai
Available date2023-02-12T09:23:34Z
Publication Date2022-11-01
Publication NameEngineering Applications of Artificial Intelligence
Identifierhttp://dx.doi.org/10.1016/j.engappai.2022.105349
CitationCheng, W. X., Gao, R., Suganthan, P. N., & Yuen, K. F. (2022). EEG-based emotion recognition using random Convolutional Neural Networks. Engineering Applications of Artificial Intelligence, 116, 105349.‏
ISSN09521976
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85137166921&origin=inward
URIhttp://hdl.handle.net/10576/39973
AbstractEmotion recognition based on electroencephalogram (EEG) signals is helpful in various fields, including medical healthcare. One possible medical application is to diagnose emotional disorders in patients. Humans tend to work and communicate efficiently when in a good mood. On the other hand, negative emotions can harm physical and mental health. Traditional EEG-based methods usually extract time-domain and frequency-domain features before classifying them. Convolutional Neural Networks (CNN) enables us to extract features and classify them end-to-end. However, most CNN methods use backpropagation to train their models, which can be computationally expensive, primarily when a complex model is used. Inspired by the successes of Random Vector Functional Link and Convolutional Random Vector Functional Link, we propose using a randomized CNN model for emotion recognition that removes the need for a backpropagation method. Also, we expand our randomized CNN method to a deep and ensemble version to improve emotion recognition performance. We do experiments on the commonly used publicly available Database for Emotion Analysis using the Physiological Signals (DEAP) dataset to evaluate our randomized CNN models. Results on the DEAP dataset show our models outperform all other models, with at least 95% accuracy for all subjects. Our ensemble version outperforms our shallow version, winning the shallow version in most subjects.
Languageen
PublisherElsevier Ltd
SubjectConvolutional Neural Networks
Deep learning
Emotion recognition
Randomized neural networks
TitleEEG-based emotion recognition using random Convolutional Neural Networks
TypeArticle
Volume Number116
dc.accessType Abstract Only


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