Table 5.

Important passive hybrid brain–computer interface studies for drowsiness detection (from 2010 to 2016).

Reference	Brain area	Modality	Application	Analysis type	Classifier	Commands	Accuracy (%)	Window size (s)
Khushaba et al. (2011)	Frontal and occipital	Electroencephalography (EEG) + electrooculography (EOG) + ECG	Driver drowsiness detection	Online	Linear discriminant analysis (LDA), support vector machine (SVM), K-nearest neighbor, and kernel SVM	1	95−97	10
Chen et al. (2015)	Frontal and occipital	EEG + EOG	Automatic detection of drowsiness	Online	ELM	2 (single command for drowsiness)	97.3	8
Ahn et al. (2016)	Whole brain	EEG + NIRS	Mental fatigue level estimation	Online	LDA	1	75.9	60