EMG

Stable Responsive EMG Sequence Prediction and Adaptive Reinforcement with Temporal Convolutional Networks

Author(s): Joseph L. Betthauser, John T. Krall, Shain G. Bannowsky, Gyorgy Levay, Rahul R. Kaliki, Matthew S. Fifer, Nitish V. Thakor
Stable Responsive EMG Sequence Prediction and Adaptive Reinforcement with Temporal Convolutional Networks 170 177 IEEE Transactions on Biomedical Engineering (TBME)
Movement prediction from EMG can be performed by compressing a short window of EMG into a feature-encoding that is meaningful for classification— an approach that can cause erratic prediction behavior. Temporal convolutional networks (TCN) leverage temporal information from EMG to achieve superior predictions for 3 simultaneous degrees-of-freedom that are more accurate and stable, have a very low response delay, and allow for novel types of interactive training. Addressing EMG decoding as a sequential prediction problem requires a new set of considerations that will lead to enhancements in the reliability, responsiveness, and movement complexity available from prosthesis control systems. read more

Is EMG a Viable Alternative to BCI for Detecting Movement Intention in Severe Stroke?

Author(s): Sivakumar Balasubramanian, Eliana Garcia-Cossio, Niels Birbaumer, Etienne Burdet, Ander Ramos-Murgialday
Is EMG a Viable Alternative to BCI for Detecting Movement Intention in Severe Stroke? 170 177 IEEE Transactions on Biomedical Engineering (TBME)

EEG-based brain-computer interface (BCI) has been used to detect movement intention in severely affected stroke patients during assisted therapy, but current EEG-BCI systems are not practical for routine clinical use.…

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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): 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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