中文摘要：

为了提髙人体上肢动作识别正确率,提出了一种基于表面肌电信号双谱分析的动作分类方法,以信息增益 作为表面肌电信号起止点分割效果衡量标准,结合TKE 算子提取出肌肉运动起止区间的表面肌电信号,对提取到 的表面肌电信号进行双谱变换,提取双谱的正反对角切片作为表面肌电信号特征,以概率神经网络作为分类器,以 100次 10折交叉验证为一次动作分类实验,计算 10次分类实验的平均正确率,最终得到正对角切片、反对角切片 和正反对角切片的分类正确率分别为94. 56%、 90. 93% 和 95.48 % .

英文摘要：

In order to improve the accuracy of upper limb movement recognition,an action classification method based on bispectrum analysis of surface EMG signals was presented in this paper. Information gain was used as the measure criterion of the surface EMG start and end signal segmentation. The segmented signal was extracted by the TKE operator, then the extracted signals were bispectrum- transformed ,and bispectrum slices were extracted as the surface EMG features. The probabilistic neural network was used as the classifier, with 100 times 10-fold cross validation as an action classification experiment,and the average correct rate of 10 times was calculated. The correct rates of classification for diagonal slices,secondary diagonal slices and bi-diagonal slices were 94. 5 6 % ,90. 83 % and 95. 4 8 % respectively.