Amputee

Automatic control of prosthetic socket size for people with transtibial amputation: Implementation and Evaluation
Author(s)3: Ethan J. Weathersby, Joseph L. Garbini, Brian G. Larsen, Jake B. McLean, Andrew C. Vamos, Joan E. Sanders
Automatic control of prosthetic socket size for people with transtibial amputation: Implementation and Evaluation 170 177 IEEE Transactions on Biomedical Engineering (TBME)
People wearing a lower leg prosthesis often experience discomfort or pain during the day because of changes in socket fit. To solve this problem, we created a motor-actuated prosthetic socket that automatically maintains socket fit by continuous adjustment of the socket size. A proportional-integral (PI) control system is implemented to adjust socket size based on data collected from an inductive sensor embedded within the socket wall. The sensed distance is representative of limb-to-socket distance. Experiments on participants with transtibial limb amputation verify that the system properly maintains and responds to a change in set point to maintain socket fit. read more

Stable Responsive EMG Sequence Prediction and Adaptive Reinforcement with Temporal Convolutional Networks
Author(s)3: 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
A New Modeling Method to Characterize the Stance Control Function of Prosthetic Knee Joints

A New Modeling Method to Characterize the Stance Control Function of Prosthetic Knee Joints
Author(s)3: Jan Andrysek, Jessica Tomasi, Matthew Leineweber, Arezoo Eshraghi
A New Modeling Method to Characterize the Stance Control Function of Prosthetic Knee Joints 170 177 IEEE Transactions on Biomedical Engineering (TBME)

Biomechanical models can inform design and optimization of prosthetic devices by connecting empirically-derived biomechanical data to device design parameters. A new method is presented to characterize the function of prosthetic…

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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)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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