IEEE Transactions on Biomedical Engineering contains basic and applied papers dealing with biomedical engineering. Papers range from engineering development in methods and techniques with biomedical applications to experimental and clinical investigations with engineering contributions.
Joseph L. Betthauser
J. L. Betthauser is with the Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218 USA.
TBME, Featured ArticlesLimb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations from Extreme Learning
Joseph L. Betthauser, Christopher L. Hunt, Luke E. Osborn, Matthew R. Masters, Gyorgy Levay, Rahul R. Kaliki, Nitish V. Thakor
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 that influence the EMG signals, hindering the ability of pattern... Read more
Posted on 25 MAR 2018
TBME, Featured ArticlesStable Responsive EMG Sequence Prediction and Adaptive Reinforcement with Temporal Convolutional Networks
Joseph L. Betthauser, John T. Krall, Shain G. Bannowsky, Gyorgy Levay, Rahul R. Kaliki, Matthew S. Fifer, Nitish V. Thakor
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
Posted on 29 MAY 2020