myoelectric

Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations from Extreme Learning

Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations from Extreme Learning

Author(s)3: Joseph L. Betthauser, Christopher L. Hunt, Luke E. Osborn, Matthew R. Masters, Gyorgy Levay, Rahul R. Kaliki, Nitish V. Thakor
Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations from Extreme Learning 170 177 IEEE Transactions on Biomedical Engineering (TBME)

Electromyogram (EMG) signals can be used to decode the intended movements of an amputee for control of a dexterous upper-limb prosthesis. However, normal prosthesis use involves changes in upper-limb positions…

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