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由于运动神经系统本质上是一个高度非线性的动力学系统 ,尝试提取肌电信号的非线性动力学信息作为信号的特征。方法采用一种算法简单、适合短数据运算的复杂度算法 ,提取双通道表面肌电信号的复杂度信息来反映运动神经系统运动的复杂程度。结果比较了 4种前臂动作信号的复杂度指标 ,具有很好的分离性。结论该算法能够满足实时处理的要求 ,作为一种新的肌电信号量化特征 ,复杂度指标为生理与病理分析、运动模式分类提供了新的思路。
Since the motor system is essentially a highly nonlinear dynamical system, it attempts to extract the nonlinear dynamic information of the EMG signal as a feature of the signal. Methods A complex algorithm which is simple in algorithm and suitable for short data operation is used to extract the complexity information of dual-channel surface EMG signals to reflect the complexity of motility of motor system. Results The comparisons of the four kinds of forearm motion signal complexity index, with good separation. Conclusion The proposed algorithm can meet the requirements of real-time processing. As a new quantitative feature of EMG signal, the complexity index provides a new idea for physiological and pathological analysis and classification of exercise patterns.