Study on How Patients With Lower Limb Amputations Anticipate Walking on Slopes and Stairs to Improve Prosthesis Control

What this Trial Is About

Researchers are studying how people with lower limb amputations use prostheses to navigate complex movements like climbing and descending stairs or slopes. Current prostheses adjust movement only after the first step, but this study aims to understand and describe anticipatory locomotor behaviors to improve safety and ease of movement. The research focuses on using supervised machine learning to classify walking behaviors and joint and muscle movement characteristics during these tasks. The ultimate goal is to develop an autonomous sensor system to control prosthesis behavior based on anticipation. The study involves observing patients with unilateral lower limb amputations who use prostheses regularly, as well as healthy volunteers. Participants will undergo various functional tests such as 2-minute, 200-metre, and 400-metre walking tests. They will also receive 3D analyses of walking and balance, including assessments of trunk and lower limb muscle strength. These evaluations will help describe the locomotor adaptations for walking on slopes and stairs. Participants will be assessed over a period of two months, during which researchers will monitor the accuracy of the machine learning algorithm in classifying locomotor behavior. The study includes collecting data on walking patterns, muscle activity, and balance. This observational study does not involve experimental treatments but focuses on detailed movement analysis to develop better prosthetic control. Individuals will be regularly evaluated to measure the algorithms error rate and to understand locomotor expectations.

Study of Locomotor Expectations for Ascending/Descending Slope and Stairs in Patients With Limb Amputations