Evaluating interface pressure in a lower-limb prosthetic socket: Comparison of FEM and experimental measurements on a roll-over simulator.

Improper socket fitting in lower-limb prostheses can lead to significant complications, including pain, skin lesions, and pressure ulcers. Current suspension and socket design practices rely predominantly on visual inspection of the residual limb and patient feedback. Monitoring stress distribution at the residual limb/socket interface offers a more objective approach.

Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices-A Systematic Review.

Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device.