PSD-CNN Approach for Subject Independent Dementia Recognition from EEG Signals
3
Issued Date
2024-01-01
Resource Type
Scopus ID
2-s2.0-85201435706
Journal Title
Proceedings - 21st International Joint Conference on Computer Science and Software Engineering, JCSSE 2024
Start Page
588
End Page
594
Rights Holder(s)
SCOPUS
Bibliographic Citation
Proceedings - 21st International Joint Conference on Computer Science and Software Engineering, JCSSE 2024 (2024) , 588-594
Suggested Citation
Kongwudhikunakorn S., Kiatthaveephong S., Thanontip K., Leelaarporn P., Dujada P., Yagi T., Senanarong V., Saengmolee W., Wilaiprasitporn T. PSD-CNN Approach for Subject Independent Dementia Recognition from EEG Signals. Proceedings - 21st International Joint Conference on Computer Science and Software Engineering, JCSSE 2024 (2024) , 588-594. 594. doi:10.1109/JCSSE61278.2024.10613730 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/100592
Title
PSD-CNN Approach for Subject Independent Dementia Recognition from EEG Signals
Corresponding Author(s)
Other Contributor(s)
Abstract
Several studies of EEG-based dementia classification were conducted on the subject-dependent scenarios, which could not be a common ground truth for the new subjects, as EEG has high variability across different subjects. Thus, this work aims to propose our method based on power spectral features and convolutional neural network compared to the state-of-the-art deep learning and machine learning techniques for subject-independent dementia recognition with a leave-two-out cross-validation approach. All of the methods tested their binary classification performance on two datasets: (i) normal vs. dementia and (ii) normal vs. abnormal groups across three tasks (i.e., eyes-closed, eyes-opened, and mental imagery). The proposed method accomplished the highest performance against the state-of-the-art methods on both datasets. The eyes-closed provided the best classification result at an accuracy of 0.89 ± 0.03. Our result presents a promising future to apply the PSD-CNN method for dementia screening application.