基于模态注意力图卷积特征融合的EEG和fNIRS情感识别
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赵卿,张雪英,陈桂军,张静
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EEG and fNIRS emotion recognition based on modality attention graph convolution feature fusion
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Qing ZHAO,Xue-ying ZHANG,Gui-jun CHEN,Jing ZHANG
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| 表 3 模态注意力多路图卷积融合模型消融实验结果 |
| Tab.3 Experimental results of ablation of modality attention multi-path graph convolution fusion model |
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| 特征组合 | Acc(Std)/% | | CF | SF | GF | MA-GF | MP-GF | MA-MP-GF | | EEG(DE)+HbO+HbR | 91.77(4.31) | 92.39(4.27) | 94.93(3.12) | 95.81(2.78) | 96.11(2.50) | 96.83(2.13) | | EEG(PSD)+HbO+HbR | 89.87(3.84) | 89.11(4.91) | 92.15(3.99) | 93.83(3.34) | 94.80(2.44) | 95.71(2.14) | | EEG(DE)+HbO | 90.92(4.90) | 90.39(5.09) | 94.45(3.48) | 94.90(3.37) | 95.04(3.24) | 95.62(3.12) | | EEG(DE)+HbR | 91.30(4.71) | 90.63(4.94) | 94.59(3.23) | 95.03(3.33) | 95.21(2.98) | 95.76(2.89) | | EEG(PSD)+HbO | 87.05(6.03) | 85.97(7.14) | 90.57(4.99) | 91.36(4.52) | 92.28(3.70) | 92.94(3.48) | | EEG(PSD)+HbR | 87.96(5.46) | 86.24(6.16) | 90.63(4.72) | 91.82(4.15) | 92.88(3.48) | 93.60(3.25) |
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