Table 8.

State-of-the-art algorithms for emotion recognition.

Reference	Signals	Number of Categories	Method	Accuracy
Machot et al. [22]	EDA	4 (Emotions)	CNN	0.81
Santamaria et al. [23]	ECG, EDA	2 (Valence)	DCNN	0.75
		2 (Arousal)		0.76
Rayatdoost et al. [24]	EEG, Faces	2 (Valence)	MGIF	0.75
		2 (Arousal)		0.74
Siddharth et al. [25]	EEG, Faces	4 (Emotions)	VGG-16, LSTM	0.54
Comas et al. [27]	EDA, Faces, ECG	7 (Emotions)	BMMN-BAE-2	0.64
Our study	EDA, Faces	8 (Emotions)	DRER	0.89