Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels

• Main Authors: Rashid, Mamunur, Mahfuzah, Mustafa, Norizam, Sulaiman, Nor Rul Hasma, Abdullah, Rosdiyana, Samad
• Format: Article
• Language: English
• Published: International Information and Engineering Technology Association 2021
• Subjects: T Technology (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/33117/1/Random%20subspace%20K-NN%20based%20ensemble%20classifier%20for%20driver%20fatigue%20detection%20utilizing%20selected%20EEG%20channels.pdf; http://umpir.ump.edu.my/id/eprint/33117/; https://doi.org/10.18280/ts.380501; https://doi.org/10.18280/ts.380501

Nowadays, many studies have been conducted to assess driver fatigue, as it has become one of the leading causes of traffic crashes. However, with the use of advanced features and machine learning approaches, EEG signals may be processed in an effective way, allowing fatigue to be detected promptly a...