Table 2.
Model performance using LOSO cross-validation. * indicates P < 0.05, ** indicates P < 0.01, and *** indicates P < 0.001. Boldface indicates the best performance for each dataset and metric.
| Dataset | Metric | DGCNN/% | ACRNN/% | TSception/% | Conformer/% | LGGNet/% | Deformer/% | miMamba/% | Ours/% |
|---|---|---|---|---|---|---|---|---|---|
| DEAP | Arousal | 57.12 ± 9.81 | 57.73 ± 15.62** | 59.76 ± 10.58 | 62.30 ± 11.80 | 60.84 ± 7.94 | 60.36 ± 9.93 | 52.77 ± 6.53*** | 61.29 ± 12.54 |
| Valence | 56.63 ± 8.95 | 55.31 ± 9.14*** | 55.39 ± 7.78 | 58.51 ± 5.65 | 58.25 ± 4.30 | 57.75 ± 4.58 | 50.22 ± 3.11*** | 58.80 ± 6.90 | |
| DREAMER | Arousal | 57.93 ± 8.17 | 58.75 ± 7.21*** | 58.73 ± 6.81 | 59.41 ± 6.64 | 59.92 ± 8.83 | 59.57 ± 8.14 | 49.94 ± 6.46*** | 61.96 ± 5.85 |
| Valence | 61.26 ± 7.29 | 61.58 ± 7.19** | 64.60 ± 6.68 | 63.46 ± 8.29 | 63.63 ± 7.80 | 64.43 ± 8.12 | 45.86 ± 5.00*** | 65.11 ± 7.21 | |
| CEED | H/N/S | 56.81 ± 8.30 | 58.23 ± 15.37 | 58.08 ± 9.91 | 59.32 ± 9.24 | 59.00 ± 8.70 | 58.86 ± 9.68 | 33.91 ± 2.53*** | 59.59 ± 9.75 |
LOSO, leave-one-subject-out; DGCNN, dynamical graph convolutional neural network, ACRNN, attention-based convolutional recurrent neural network; H/N/S, happy/neutral/sad