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Background Current clinical myoelectric systems provide unnatural prosthesis control, with limited functionality. In this study, we propose a proportional state-based control method, which allows switching between functions in a more natural and intuitive way than the traditional co-contraction switch method. Methods We validated the ability of the proposed system to provide precise control in both...
A new signal processing scheme is presented for extracting neural control information from the multi-channel surface electromyographic signal (sEMG). The extracted information can be used to proportionally control a multi-degree of freedom (DOF) prosthesis. Four time-domain (TD) features were extracted from the multi-channel sEMG during a series of anisotonic, isometric wrist contractions, which involved...
A novel signal processing approach for surface electromyogram (EMG) is proposed to estimate the forces produced at multiple degree of freedom (DOF) simultaneously during dynamic voluntary contractions. The method is based on a generative model of surface EMG, and the estimation algorithm is a modified non-negative matrix factorization (NFM). The proposed method has potential to provide simultaneous...
It has often been assumed in EMG modeling and signal processing applications, that the motor unit action potential trains (MUAPT) of concurrently active motor units during voluntary contractions are not correlated. However, motor unit synchrony, or motor unit innervation process (MUIP) correlation, which implies MUAPT correlation, has been accepted as a common phenomenon in voluntary contractions...
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