DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography
Joint Authors
Wang, Yingdong
Wu, Qingfeng
Wang, Chen
Ruan, Qunsheng
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-08
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
In the past few decades, identification recognition based on electroencephalography (EEG) has received extensive attention to resolve the security problems of conventional biometric systems.
In the present study, a novel EEG-based identification system with different entropy and a continuous convolution neural network (CNN) classifier is proposed.
The performance of the proposed method is experimentally evaluated through the emotional EEG data.
The conducted experiment shows that the proposed method approaches the stunning accuracy (ACC) of 99.7% on average and can rapidly train and update the DE-CNN model.
Then, the effects of different emotions and the impact of different time intervals on the identification performance are investigated.
Obtained results show that different emotions affect the identification accuracy, where the negative and neutral mood EEG has a better robustness than positive emotions.
For a video signal as the EEG stimulant, it is found that the proposed method with 0–75 Hz is more robust than a single band, while the 15–32 Hz band presents overfitting and reduces the accuracy of the cross-emotion test.
It is concluded that time interval reduces the accuracy and the 15–32 Hz band has the best compatibility in terms of the attenuation.
American Psychological Association (APA)
Wang, Yingdong& Wu, Qingfeng& Wang, Chen& Ruan, Qunsheng. 2020. DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1139573
Modern Language Association (MLA)
Wang, Yingdong…[et al.]. DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1139573
American Medical Association (AMA)
Wang, Yingdong& Wu, Qingfeng& Wang, Chen& Ruan, Qunsheng. DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1139573
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139573