Abstract
As modern medicine has improved, the average age of patients has increased. This has cause a growing number of patients to develop disabilities over time due to spinal cord injuries and stroke among other neurological ailments. This has led to an increased interest in developing robotic exoskeletons to help patients with neuromuscular rehabilitation. However, most exoskeletons do not accurately replicate the natural human gait kinematics due to a lack of degrees of freedom at the designed knee joint. In this thesis, the leg assembly for a robotic rehabilitation (RoboREHAB) device is redesigned to improve the gait kinematics and a reinforcement learning (RL) based controller is designed to control the new leg assembly using motion capture data. The new leg assembly and RL controller performed with a 5% margin of error from the motion capture data. Further improvements will be made to construct a full-scale prototype and establish real-time data acquisition.
Date of publication
Spring 5-15-2024
Document Type
Thesis
Language
english
Persistent identifier
http://hdl.handle.net/10950/4692
Committee members
Chung-Hyun Goh, Alwathiqbellah Ibrahim, Mohammad Biswas, Mukul Shirvaikar
Degree
Master of Science in Mechanical Engineering
Recommended Citation
Anthony, Jacob, "REDESIGN OF LEG ASSEMBLY FOR REMOTE WALKING TRAINING DEVICE TO IMPROVE GAIT KINEMATICS" (2024). Mechanical Engineering Theses. Paper 30.
http://hdl.handle.net/10950/4692