APPLICATION OF BLIND SIGNAL PROCESSING TECHNIQUE TO TWO-CHANNEL UPPER LIMB MYOELECTRIC SIGNAL IDENTIFICATION PROBLEM
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摘要: 根据肌电信号产生机理，本文对双通道前臂肌电信号建立单输入多输出FIR系统模型，由于模型输入未知且不可测，采用了盲信号处理方法对模型参数进行辨识．通过提取模型冲激响应作为信号特征，能够对握拳、展拳、前臂内旋和前臂外旋四类前臂动作进行识别．实验表明，该方法仅需建立较低阶数的模型即可达到较好的分类目的，性能要优于传统的AR模型方法．Abstract: According to the physiology of myoelectric signals, a two-channel single input multiple output (SIMO) FIR model is proposed to the two-channel upper limb EMG signal in this paper. As the input of the model is unknown and unaccessible, blind signal processing technique is employed to identify the model parameters. After extracting two channels'impulse responses, four types of forearm motions, i.e. hand grasp, hand extension, forearm supination and forearm pronation are able to be classified. Experimental results demonstrate that this method has a better classification result than the classical AR parameter method. This paper shows a promising application of blind signal processing method to the analysis of physiological signals.
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Keywords:
- blind signal processing /
- blind channel identification /
- EMG /
- pattern recognition
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