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

Mental fatigue is a psychophysical condition with significant adverse effect on daily life, compromising both physical and mental wellness. We are experiencing challenges in this fast-changing environment, problems becoming more prominent. This demands an urgent need to explore effective accurate automated system for timely detection. Therefore, we present systematic review of brain-computer interface (BCI) studies detection using artificial intelligent (AI) techniques published Scopus, IEEE Explore, PubMed Web Science (WOS) between 2011 2022. The Boolean search expression that comprised (((ELECTROENCEPHALOGRAM) AND (BCI)) (FATIGUE CLASSIFICATION)) (BRAIN-COMPUTER INTERFACE) has been used select the articles. Through Preferred Reporting Items Systematic Reviews Meta-Analysis (PRISMA) methodology, selected 39 out 562 Our identified research gap employing BCI intervention through neurofeedback. summarized AI employed develop EEG-based discussed. have presented comprehensive future recommendations from gaps discussions. direction includes data fusion, hybrid classification models, availability public datasets, uncertainty, explainability, hardware implementation strategies.