SOURCE RECORD / S0158
Driving drowsiness detection using spectral signatures of EEG-based neurophysiology
Driving drowsiness detection using spectral signatures of EEG-based neurophysiology
- Authors or organization
- Arif et al.
- Published date
- 2023
- Source type
- peer_reviewed_human_study
- Technology route
- noninvasive EEG
- Function or setting
- drowsiness detection
- Rights status
- manual_review / CC BY (version unspecified)
Evidence summary
Evidence: Within-pooled-data drowsiness classification. Key figures: 6 EEG channels; merged 10-second windows; random 10-fold; feature selection on pooled participants. Limitations: No participant or session grouping; identity adjacent-window and global-selection leakage; male simulated-driving sample cannot support cross-person real-world generalization.
Key figures
6 EEG channels; merged 10-second windows; random 10-fold; feature selection on pooled participants
Limitations
No participant or session grouping; identity adjacent-window and global-selection leakage; male simulated-driving sample cannot support cross-person real-world generalization