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 3 所提方法与对比文献的分类准确率对比

Tab.3 Comparison of classification accuracy between proposed method and comparative references

被试者 A/% 本研究方法 DFFN[30] HC-CNN[31] PSO-CNN[32] CNN-LSTM[33] SS-MEMDBF[35] RBM-SVM[36] ETRCNN[37] 1 99.14 85.40 90.07 93.30 98.82 91.49 86.61 85.88 2 99.49 69.30 80.28 84.59 98.64 60.56 61.26 75.41 3 99.68 90.29 97.08 91.68 96.92 94.16 87.27 91.32 4 99.01 71.07 89.66 84.55 96.50 76.72 75.20 83.45 5 99.61 65.41 97.04 86.54 92.75 58.52 64.55 72.11 6 98.86 69.45 87.04 76.92 91.84 68.52 65.91 91.72 7 98.58 88.18 92.14 94.03 95.07 78.67 83.78 85.71 8 99.82 86.46 98.51 93.20 95.25 97.01 89.91 91.32 9 98.98 93.54 92.31 92.24 99.23 93.85 92.08 93.23 平均值 99.24 79.90 91.57 85.56 96.13 79.94 78.51 85.57 均方差 0.3998 10.25 5.41 5.46 2.486 14.13 11.29 7.08