Akshansh, Gupta and R. K., Agrawal and Jyoti Singh, Kirar and Baljeet, Kaur and Weiping, Ding and Chin-Teng, Lin and Andreu-Perez, Javier and Mukesh, Prasad (2020) A Hierarchical Meta-model for Multi-Class Mental Task Based Brain-Computer Interfaces. Neurocomputing, 389. pp. 207-217. DOI https://doi.org/10.1016/j.neucom.2018.07.094
Akshansh, Gupta and R. K., Agrawal and Jyoti Singh, Kirar and Baljeet, Kaur and Weiping, Ding and Chin-Teng, Lin and Andreu-Perez, Javier and Mukesh, Prasad (2020) A Hierarchical Meta-model for Multi-Class Mental Task Based Brain-Computer Interfaces. Neurocomputing, 389. pp. 207-217. DOI https://doi.org/10.1016/j.neucom.2018.07.094
Akshansh, Gupta and R. K., Agrawal and Jyoti Singh, Kirar and Baljeet, Kaur and Weiping, Ding and Chin-Teng, Lin and Andreu-Perez, Javier and Mukesh, Prasad (2020) A Hierarchical Meta-model for Multi-Class Mental Task Based Brain-Computer Interfaces. Neurocomputing, 389. pp. 207-217. DOI https://doi.org/10.1016/j.neucom.2018.07.094
Abstract
In the last few years, many research works have been suggested on Brain- Computer Interface (BCI), which assists severely physically disabled persons to communicate directly with the help of electroencephalogram (EEG) signal, generated by the thought process of the brain. Thought generation inside the brain is a dynamic process, and plenty thoughts occur within a small time window. Thus, there is a need for a BCI device that can distinguish these various ideas simultaneously. In this research work, our previous binary-class mental task classication has been extended to the multi-class mental task problem. The present work proposed a novel feature construction scheme for multi mental task classication. In the proposed method, features are
Item Type: | Article |
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Uncontrolled Keywords: | Machine Learning; Artificial Intelligence; Brain Computer Interfaces |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 19 Oct 2018 11:25 |
Last Modified: | 30 Oct 2024 16:27 |
URI: | http://repository.essex.ac.uk/id/eprint/23188 |
Available files
Filename: Article_Neurocomputing.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0