چکیده مقاله
This article introduces a novel approach to designing a reinforcement learning based control system for robot assisted rehabilitation Unlike traditional rehabilitation methods where therapists manually guide patients through exercises, our system employs intelligent agents, specifically reinforcement learning, to autonomously assist individuals in their rehabilitation journey The focus of this study is on the rehabilitation of hand muscles using a robotic exoskeleton Patients follow a desired path based on visual feedback displayed on a monitor, while the reinforcement learning control acts as an intelligent therapist, intervening when the patient deviates from the correct trajectory The control mechanism is model free, relying solely on information exchange between the agent and the environment for learning Q learning is employed as the core algorithm in this scenario, showcasing its effectiveness in facilitating smart therapy sessions
کلیدواژهها
نویسندگان
Seyedhossein Seyedhosseini
Amirkabir University of Technology Department of Electrical EngineeringTehran, Iran
شیوه ارجاع
Seyedhosseini, Seyedhossein,1402,Reinforcement Learning-Based Control for Robot-Assisted Rehabilitation,8th International Conference on Science & Technology with sustainable development approach,Tehran
ارائهشده در
مجموعه مقالات هشتمین همایش بین المللی علوم و تکنولوژی با رویکرد توسعه پایدار15 اسفند 1402 · تهران