Motor Imagery Decoding on Dataset II (cross-subject) benchmark leaderboard · SOTA2 Research

Motor Imagery Decoding on Dataset II (cross-subject)

80.52Subject Accuracy (S1)BFM-MSDA

Evaluation Results

Method	Links
BFM-MSDA2025.07		80.52	73.53	85.15	74.48	81.42	75.51	72.05	73.15	92.75	75.52	78.41	0.5682
ASJDA2025.07		79.03	69.72	78.16	69.52	67.46	72.56	64.68	78.5	89.15	72.42	74.12	0.4824
DJDAN2025.07		78.36	70.87	80.53	72.73	74.67	80.27	74.38	74.54	90.12	70.94	76.74	0.5348
JAN2025.07		78.27	71.38	80.72	73.75	79.46	76.84	73.05	70.3	87.35	70.28	76.14	0.5228
Conformer2025.07		77.62	71.01	78.8	74.12	78.99	66.83	74.09	71.09	81.92	69.69	74.42	0.4883
DJP-MMD2025.07		76.31	74.43	78.26	71.85	73.62	77.94	70.22	71.43	82.45	71.52	74.8	0.4961
GAT2025.07		76.25	71.36	83.73	69.32	77.45	75.73	74.84	72.84	90.45	73.64	76.56	0.5312
ShallowConvNet2025.07		73.92	67.63	75.05	71.55	75.23	63.65	70.56	67.7	78.02	66.37	70.97	0.4194
EEGNet2025.07		66.57	60.96	82.7	70.14	73.89	59.05	55.68	63.56	88.29	65.06	68.59	0.3718
CBraMod w/ Linear2025.07		61.37	57.09	66.98	55.45	61.96	60.58	59.87	58.27	72.36	58.91	61.29	0.2257
LaBraM w/ Linear2025.07		56.72	55.68	64.34	58.63	62.37	60.28	57.41	60.46	66.34	57.15	59.94	0.1988