Towards Efficient Personalization of Computerized Lower Limb Prostheses Via Reinforcement Learning in a Clinical Setup - Patient Study
Towards Efficient Personalization of Computerized Lower Limb Prostheses Via Reinforcement Learning in a Clinical Setup - Patient Study
The goal of this clinical trial is to understand the feasibility and effectiveness of using reinforcement learning to personalize robotic prosthetic legs (an experimental prototype) for unilateral transfemoral amputees. The main questions it aims to answer are:
Participants will go through the standard prosthetic fitting procedures, such as alignment adjustment, then they will experience repeated prosthesis personalization procedures conducted by tuning specialists without RISE, tuning specialists with RISE, and prosthetists (without tuning expertise) with RISE on different types of terrains. In the end, the participants will go through a testing trial, in which they will experience the prototype personalized through the three different approaches without knowing how the control parameters are decided. Their walking performance will be recorded. It is expected that the participants will visit the testing site 8 times, which including alignment (1 visit), three personalization procedures (twice for each), and one testing trial (1-2 visits).
Inclusion Criteria:
Exclusion Criteria:
mliu10@ncsu.edu9195158541
lasmith6@ncsu.edu919-513-3840