Review on EEG-Based Authentication Technology

Table 4

Deep learning methods for EEG-based authentication.

Research	Tasks	Number of subjects	Number of electrodes	Deep learning model	Accuracy (%)
Sun et al. [72]	Resting state	109	16	LSTM	99.58
Mao et al. [50]	ERP	100	64	CNN	97.00
Wang et al. [24]	Resting state	109	64	GCNN	99.98
Das et al. [37]	MI	40	17	CNN	99.30
Wilaiprasitporn et al. [71]	ERP with emotion			CNN ＋ RNN	99.90
Chen et al. [58]	ERP	100		GSLT-CNN	97
	RSVP	10			99
	ERP with emotion	32			99
	Multiple data sets	157			96
Zhang et al. [26]	Resting state	8	14	Attention-based RNN	98.20
	MI	8	64		99.89
Wu et al. [34]	RSVP with eye blinking	10	16	CNN	97.60
Kumar et al. [29]	VEP	58	14	LSTM	97.57
Wang et al. [73]	SSVEP	10	8	CNN	99.73