基于卷积神经网络的多类运动想象脑电信号识别

刘近贞,叶方方,熊慧

Recognition of multi-class motor imagery EEG signals based on convolutional neural network

Jin-zhen LIU,Fang-fang YE,Hui XIONG

表 4 所提方法与对比文献分类Kappa值对比

Tab.4 Comparison of classification Kappa value between proposed method and comparative references

被试者 Kappa值 所提方法 CNN-LSTM[33] RBM-SVM[36] ETRCNN[37] C2CM[38] 3D-CNN[39] FBCSP[40] 1 0.9885 0.8500 0.8214 0.8420 0.8750 0.6990 0.6800 2 0.9933 0.5400 0.4838 0.6630 0.6528 0.4590 0.4200 3 0.9957 0.8700 0.7696 0.8770 0.9028 0.7880 0.7500 4 0.9863 0.7800 0.6664 0.7610 0.6667 0.5940 0.4800 5 0.9948 0.7700 0.5024 0.5710 0.6250 0.6470 0.4000 6 0.9848 0.6600 0.5301 0.8910 0.4549 0.5380 0.2700 7 0.9810 0.9500 0.7837 0.8090 0.8959 0.6530 0.7700 8 0.9976 0.8300 0.8655 0.8900 0.8333 0.7020 0.7600 9 0.9864 0.9000 0.8942 0.9070 0.7951 0.7130 0.6100 平均值 0.9898 0.7944 0.7019 0.8012 0.7446 0.6437 0.5711 均方差 0.0053 0.1197 0.1518 0.1097 0.1446 0.0942 0.1737