In our present work, the sample entropy (SampEn) was used to analyze the changes of ship driver driving fatigue state when they drive for a long time from the perspective of human electroencephalogram (EEG). Combining with the eye movement, the law of fatigue change caused by long-time driving of the ship is analyzed. Thus, it can conclude that the EEG characteristics, as well as the eye movement, can effectively detect driver’s fatigue when they are driving.
Real-time EEG-based detection of ship driving fatigue using sample entropy
Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) ; 2022 ; Wuhan,China
Proc. SPIE ; 12610
28.04.2023
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Study of Steering Wheel Movement under Fatigue Driving and Drunk Driving Based on Sample Entropy
British Library Conference Proceedings | 2015
|A Fatigue Driving Detection Algorithm Based on Facial Motion Information Entropy
DOAJ | 2020
|Accurate Real-time Ship Target detection Using Yolov4
IEEE | 2021
|Near Real Time Ship Detection Experiments
British Library Conference Proceedings | 2010
|Research on Real-Time Ship Detection Using Deep Learning
IEEE | 2022
|