Table 5.

Within-subject Classification accuracies averaged on 10-folds.

	CSP		FBCSP		MDRM		ShallowNet		EEGNet***
	w/o PS	w/ PS	w/o PS	w/ PS	w/o PS	w/ PS	w/o PS	w/ PS	w/o PS	w/ PS
BNCI2014001	0.68	0.66	0.70	0.72	0.68	0.68	0.76	0.77	0.78	0.79
BNCI2014004	0.70	0.69	0.74	0.75	0.69	0.69	0.79	0.79	0.79	0.80
PhysionetMI	0.56	0.56	0.59	0.61	0.57	0.57	0.53	0.56	0.51	0.56
Cho2017	0.57	0.57	0.60	0.59	0.58	0.58	0.68	0.68	0.65	0.66
Weibo2014	0.66	0.65	0.68	0.69	0.68	0.65	0.75	0.76	0.71	0.74
Zhou2016	0.81	0.82	0.89	0.88	0.80	0.82	0.83	0.87	0.84	0.88
CBCIC2019001	0.57	0.55	0.60	0.60	0.59	0.57	0.66	0.66	0.71	0.71
CBCIC2019004	0.69	0.69	0.74	0.73	0.70	0.70	0.65	0.65	0.62	0.65
Mean	0.65	0.65	0.69	0.70	0.66	0.66	0.71	0.72	0.70	0.72

Stars correspond to ^***p < 0.01. The boldface shows that the accuracy of method with pre-alignment strategy (w/ PS) is higher than that without pre-alignment strategy (w/o PS).