EEG Emotion Recognition on SEED
96.55AccuracyMVGT-F
Evaluation results
| Method | Links | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MVGT-FScheme=FRONTAL2024.07 | 96.55 | 4.18 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| PRISMTechnique=Dynamic, Mode=Dependent2026.07 | 96.52 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| EEG-CSANetYear=20252025.12 | 96.03 | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.9404 | — | |
| MVGT-LScheme=LOBE2024.07 | 96.01 | 4.85 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MVGT-GScheme=GENERAL2024.07 | 95.82 | 4.43 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MVGT-HScheme=HEMISPHERE2024.07 | 95.79 | 4.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CU-GCNYear=20242025.12 | 95.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| V-IAGYear=20212025.12 | 95.64 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MV-SSTMA2024.07 | 95.32 | 3.05 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| EEG-ConformerYear=20232025.12 | 95.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.9295 | — | |
| EmoGT2024.07 | 95.02 | 5.99 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CWGCNTechnique=Dynamic, Mode=Dependent2026.07 | 94.97 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MD-AGCN2024.07 | 94.81 | 4.52 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| PGCNProtocol=Subject-dependent, Scheme=9:62025.02 | 94.3 | 6.19 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RGNNProtocol=Subject-dependent, Scheme=9:62025.02 | 94.24 | 5.95 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RGNN2024.07 | 94.24 | 5.95 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| R2G-STNN2024.07 | 93.34 | 5.96 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| FATProtocol=Subject-dependent, Scheme=9:6, Configuration=w/ FAN2025.02 | 93.18 | 11.28 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| PRISMTechnique=Semi-supervised, Mode=Independent2026.07 | 93.17 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BiHDM2024.07 | 93.12 | 6.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BiHDMProtocol=Subject-dependent, Scheme=9:62025.02 | 93.07 | 8.39 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| GDDNTechnique=Graph, Mode=Independent2026.07 | 92.54 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BiDANN2024.07 | 92.38 | 7.04 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| FATProtocol=Subject-dependent, Scheme=9:6, Configuration=ours2025.02 | 92.1 | 6.46 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| GUSATechnique=Unsupervised, Mode=Independent2026.07 | 91.77 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MS-iMambaInput=Raw, Channels=42024.09 | 91.36 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| EEGMatchTechnique=Semi-supervised, Mode=Independent2026.07 | 91.35 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ATDD-LSTMInput=DE, Channels=All2024.09 | 91.08 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DGCNNYear=20202025.12 | 90.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.856 | — | |
| DGCNN2024.07 | 90.4 | 8.49 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CGRU-MDGNTechnique=Graph, Mode=Independent2026.07 | 90.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DGCNNInput=PSD, Channels=All2024.09 | 90.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DGCNNProtocol=Subject-dependent, Scheme=9:62025.02 | 89.75 | 8.51 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ConformerProtocol=Subject-dependent, Scheme=9:62025.02 | 88.68 | 9.97 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DS-AGCTechnique=Semi-supervised, Mode=Independent2026.07 | 87.37 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LELType=Ours2025.04 | 86.79 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 85.9 | |
| RSM-CoDGMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 86.35 | 7.17 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| miMambaTechnique=Static, Mode=Dependent2026.07 | 86.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| R2G-STNNMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 84.16 | 7.63 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SVMProtocol=Subject-dependent, Scheme=9:62025.02 | 83.99 | 8.79 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SVMYear=20152025.12 | 83.99 | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.7912 | — | |
| ARCNNTechnique=Dynamic, Mode=Dependent2026.07 | 83.93 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CSGNNInput=DE, Channels=20%2024.09 | 83.93 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DMMRMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 83.87 | 6.38 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BiDANNMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 83.28 | 9.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CSGNNTechnique=Dynamic, Mode=Independent2026.07 | 81.85 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DANNMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 81.65 | 9.92 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MS-MDAMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 81.43 | 10.17 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| KNNProtocol=Subject-dependent, Scheme=9:62025.02 | 80.88 | 9.73 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ACCNetType=Others2025.04 | 80.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 79.43 | |
| EmT-DMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 80.2 | 11.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| EmTTechnique=Transformer, Mode=Independent2026.07 | 80.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MAS-DGATMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 80.02 | 5.79 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DGCNNMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 79.95 | 9.02 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RGNNMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 79 | 14.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| FBCNetType=Others2025.04 | 77.31 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 78.26 | |
| LSTM-CNNTechnique=Attention, Mode=Independent2026.07 | 76.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| EEGNetType=Others2025.04 | 74.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 73.93 | |
| LGGNetType=Others2025.04 | 72.24 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 71.96 | |
| AMDETMethod category=Deep learning methods, Evaluation protocol=LOSO2026.01 | 72.1 | 16.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CORALMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 71.48 | 11.57 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| FC_STGNNType=Others2025.04 | 69.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 68.22 | |
| SAMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 69 | 10.84 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BF-GCNType=Others2025.04 | 68.83 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 67.91 | |
| SVMType=Traditional2025.04 | 66.84 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 66.73 | |
| Decision TreeType=Traditional2025.04 | 66.41 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 66.38 | |
| TCAMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 63.64 | 14.88 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| KNNType=Traditional2025.04 | 63.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 67.22 | |
| TAS-NetTechnique=Unsupervised, Mode=Independent2026.07 | 63.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RFMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 62.78 | 6.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| KPCAMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 61.28 | 14.62 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SVMMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 56.73 | 16.29 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| GFKMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 56.71 | 12.29 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| KNNMethod category=Traditional machine learning methods, Evaluation protocol=LOSO2026.01 | 55.26 | 12.43 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BiDANN-SProtocol=Subject-independent classification2019.07 | — | — | 63.01 | 7.49 | 63.22 | 7.52 | 63.5 | 9.5 | 73.59 | 9.12 | 73.72 | 8.67 | 84.14 | 6.87 | — | — | |
| BiHDMProtocol=Subject-independent classification2019.07 | — | — | — | — | — | — | — | — | — | — | — | — | 85.4 | 7.53 | — | — | |
| CBraModEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.6448 | — | |
| CBraModEvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.3288 | — | |
| ConformerEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.4963 | — | |
| ConformerEvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.2543 | — | |
| DANProtocol=Subject-independent classification2019.07 | — | — | — | — | — | — | — | — | — | — | — | — | 83.81 | 8.56 | — | — | |
| DGCNNProtocol=Subject-independent classification2019.07 | — | — | 49.79 | 10.94 | 46.36 | 12.06 | 48.29 | 12.28 | 56.15 | 14.01 | 54.87 | 17.53 | 79.95 | 9.02 | — | — | |
| EmTEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.5949 | — | |
| EmTEvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.3257 | — | |
| LGGNetEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.5039 | — | |
| LGGNetEvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.2275 | — | |
| MMMEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.6168 | — | |
| MMMEvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.3248 | — | |
| PGCNEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.6054 | — | |
| PGCNEvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.3115 | — | |
| PopTEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.6269 | — | |
| PopTEvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.3285 | — | |
| RECTOREvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.7187 | — | |
| RECTOREvaluation Protocol=Subject Independent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.3756 | — | |
| RGNNProtocol=Subject-independent classification2019.07 | — | — | 64.88 | 6.87 | 60.69 | 5.79 | 60.84 | 7.57 | 74.96 | 8.94 | 77.5 | 8.1 | 85.3 | 6.72 | — | — | |
| SAProtocol=Subject-independent classification2019.07 | — | — | 53.23 | 7.47 | 50.6 | 8.31 | 55.06 | 10.6 | 56.72 | 10.78 | 64.47 | 14.96 | 69 | 10.89 | — | — | |
| SVMProtocol=Subject-independent classification2019.07 | — | — | 43.06 | 8.27 | 40.07 | 6.5 | 43.97 | 10.89 | 48.63 | 10.29 | 51.59 | 11.83 | 56.73 | 16.29 | — | — | |
| T-SVMProtocol=Subject-independent classification2019.07 | — | — | — | — | — | — | — | — | — | — | — | — | 72.53 | 14 | — | — | |
| TCAProtocol=Subject-independent classification2019.07 | — | — | 44.1 | 8.22 | 41.26 | 9.21 | 42.93 | 14.33 | 43.93 | 10.06 | 48.43 | 9.73 | 63.64 | 14.88 | — | — | |
| TSceptionEvaluation Protocol=Subject Dependent2026.06 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.5699 | — |