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Classification of EMG signal on arm muscle motion using special fourier transformation to control electric wheelchair

机译:用特殊的傅里叶变换控制电动轮椅对臂肌肉运动的EMG信号分类

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Research about electromyograph (EMG)is quite popular in biomedical application. This paper present classification of EMG signal on arm muscle motion using Special Fourier Transformation to control electric wheelchair. This method is a modification of the common fourier transforms that are used to obtain the fourier component of a signal with a known frequency. Fourier component value is written on a microcontroller. At any time the ADC data retrieval is subsequently processed using a special fourier transform. Error value of the fourier component written on microcontroller with the result of the calculation at any time is used as control data to drive the electric wheelchair. The arm muscles motion that used to control the electric wheelchair are the ulna muscles, the flexor muscles of the carpi ulnaris, and bicep muscles.
机译:关于电拍摄力学的研究(EMG)在生物医学应用中非常受欢迎。本文用特殊的傅里叶变换对手臂肌肉运动对电动轮椅进行了分类。该方法是用于获得具有已知频率的信号的傅里叶组件的公共傅立叶变换的修改。傅立叶组件值写在微控制器上。随时使用特殊的傅里叶变换随后处理ADC数据检索。在微控制器上写入的傅里叶组件的误差值随着计算结果的计算结果用作驱动电动轮椅的控制数据。用于控制电动轮椅的手臂肌肉运动是尺骨肌肉,肉肉的屈肌肌肉和二头肌肌肉。

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