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A novel method for gender and age detection based on eeg brain signals
Joint Authors
Issa, Haitham
Issa, Sali
Shah, Wahab
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 5 (30 Sep. 2021), pp.704-710, 7 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-09-30
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper presents a new gender and age classification system based on Electroencephalography (EEG) brain signals.
First, Continuous Wavelet Transform (CWT) technique is used to get the time-frequency information of only one EEG electrode for eight distinct emotional states instead of the ordinary neutral or relax states.
Then, sequential steps are implemented to extract the improved grayscale image feature.
For system evaluation, a three-fold-cross validation strategy is applied to construct four different classifiers.
The experimental test shows that the proposed extracted feature with Convolutional Neural Network (CNN) classifier improves the performance of both gender and age classification, and achieves an average accuracy of 96.3% and 89% for gender and age classification, respectively.
Moreover, the ability to predict human gender and age during the mood of different emotional states is practically approved.
American Psychological Association (APA)
Issa, Haitham& Issa, Sali& Shah, Wahab. 2021. A novel method for gender and age detection based on eeg brain signals. The International Arab Journal of Information Technology،Vol. 18, no. 5, pp.704-710.
https://search.emarefa.net/detail/BIM-1431118
Modern Language Association (MLA)
Issa, Haitham…[et al.]. A novel method for gender and age detection based on eeg brain signals. The International Arab Journal of Information Technology Vol. 18, no. 5 (Sep. 2021), pp.704-710.
https://search.emarefa.net/detail/BIM-1431118
American Medical Association (AMA)
Issa, Haitham& Issa, Sali& Shah, Wahab. A novel method for gender and age detection based on eeg brain signals. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 5, pp.704-710.
https://search.emarefa.net/detail/BIM-1431118
Data Type
Journal Articles
Language
English
Notes
Text in English ; abstracts in .
Record ID
BIM-1431118