Application of Artificial Intelligence Techniques for Brain–Computer Interface in Mental Fatigue Detection: A Systematic Review (2011

Application of Artificial Intelligence Techniques for Brain–Computer Interface in Mental Fatigue Detection: A Systematic Review (2011–2022)

Author:

Yaacob Hamwira¹^ORCID,Hossain Farhad¹^ORCID,Shari Sharunizam²^ORCID,Khare Smith K.³^ORCID,Ooi Chui Ping⁴,Acharya U. Rajendra⁵

Affiliation:

1. Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia

2. College of Computing, Informatics and Media, Universiti Teknologi MARA Cawangan Kedah, Merbok, Malaysia

3. Electrical and Computer Engineering Department, Aarhus University, Aarhus, Denmark

4. School of Science and Technology, Singapore University of Social Sciences, Clementi Road, Singapore

5. School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield Central, QLD, Australia

Funder

KICT Research Initiative Grant through the Kulliyyah of Information and Communication Technology, International Islamic University Malaysia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference122 articles.

1. Single channel wireless EEG device for real-time fatigue level detection;ko;Proc Int Joint Conf Neural Netw (IJCNN),2015

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