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Deep Review of Machine Learning Techniques on Detection of Drowsiness Using EEG Signal.

Authors :
Venkata Phanikrishna, B.
Jaya Prakash, Allam
Suchismitha, Chinara
Source :
IETE Journal of Research; Jun2023, Vol. 69 Issue 6, p3104-3119, 16p
Publication Year :
2023

Abstract

Electroencephalogram (EEG) is used to analyze the state of the brain. One of the critical states of the brain is drowsiness. Physical, mental tiredness, and unconsciousness are some of the reasons for drowsiness. Drowsiness state may lead to fatal crashes, severe injury, and property damage; sometimes, it can be analyzed and detected by using EEG. Analyzing EEG signals is complicated and tedious, so an automated diagnosis is required to interpret these signals effectively. In recent years, finding drowsy feeling while working has become an important research area. In this paper, the authors reviewed various drowsiness detection techniques in the literature and analyzed the performance of 15 different machine learning algorithms for the self-acquired feature set from the EEG. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03772063
Volume :
69
Issue :
6
Database :
Complementary Index
Journal :
IETE Journal of Research
Publication Type :
Academic Journal
Accession number :
167363678
Full Text :
https://doi.org/10.1080/03772063.2021.1913070