Recent Advances in Fatigue Detection Algorithm Based on EEG
Fei Wang1,2, Yinxing Wan1, Man Li1,2, Haiyun Huang1,2, Li Li1, Xueying Hou1, Jiahui Pan1,2, Zhenfu Wen3, Jingcong Li1,2,*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3573-3586, 2023, DOI:10.32604/iasc.2023.029698
- 17 August 2022
Abstract Fatigue is a state commonly caused by overworked, which seriously affects daily work and life. How to detect mental fatigue has always been a hot spot for researchers to explore. Electroencephalogram (EEG) is considered one of the most accurate and objective indicators. This article investigated the development of classification algorithms applied in EEG-based fatigue detection in recent years. According to the different source of the data, we can divide these classification algorithms into two categories, intra-subject (within the same subject) and cross-subject (across different subjects). In most studies, traditional machine learning algorithms with artificial feature… More >