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A novel electromyographic (EMG) motion pattern classifier which combines VLR (variable learning rate) based neural network with wavelet transform and nonlinearity analysis method is presented in this paper. This motion pattern classifier can successfully identify the flexion and extension of the thumb, the index linger and the middle finger, by measuring the surface EMG signals through three electrodes...
A five-fingered underactuated prosthetic hand controlled by surface electromyographic (EMG) signals is presented in this paper. The prosthetic hand control part is based on an EMG motion pattern classifier which combines Levenberg-Marquardt (LM) or variable learning rate (VLR) based neural network with parametric autoregressive (AR) model and wavelet transform. This motion pattern classifier can successfully...
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