TY  - BOOK
AU  - Ahmed Abdelhamid Mohamed Torki
AU  - Ayman M. Eldeib , 
TI  - Automatic detection of driver drowsiness during simulated driving using brainwaves changes as indicator / 
PY  - 2018///
CY  - Cairo : 
PB  - Ahmed Abdelhamid Mohamed Torki , 
KW  - Driver drowsiness detection
KW  - Electroencephalogram
KW  - Simulated Driving
N1  - Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering; Issued also as CD
N2  - Driver drowsiness contributes widely in vehicle accidents. Studies assessed drowsiness indicators at different driving setups. The first objective was to establish an experiment to obtain generic datasets of brainwaves epochs recorded by electroencephalogram (EEG) at forehead sites labeled with alertness and drowsiness for subjects using facial expressions recorded by videos. Subjects perform simulated driving for two hours after 6 PM. The second and third objective were to extract and select significant features that yield to highest classification accuracy between alert and drowsy using statistical and classification methods. The results showed the classification accuracy was 85.8 %
UR  - http://172.23.153.220/th.pdf
ER  -