<![CDATA[This study aims to develop an IoMT Rehabilitation System based on the integration of Electromyography (EMG) sensors, embedded Internet of Medical Things (IoMT), adaptive actuators, and ergonomic design to improve the effectiveness of real-time adaptive medical rehabilitation. The study employed a Research and Development (R&D) method using a multidisciplinary approach integrating mechanical engineering, biomedical engineering, and embedded systems. The research subjects consisted of 42 participants, including mechanical engineers, biomedical engineers, rehabilitation physicians, and post-stroke patients with mild to moderate conditions. The research process included mechanical device design, prototype fabrication, EMG and IoMT sensor integration, biomechanical testing, and limited clinical validation. The results showed that the developed rehabilitation system achieved an EMG sensor reading accuracy of 94.2%, improved patient movement efficiency by 28%, and increased device comfort by 31% compared to conventional rehabilitation systems. Furthermore, the implementation of IoMT enabled real-time rehabilitation monitoring through a digital dashboard, allowing medical personnel to evaluate therapy progress more objectively and systematically. The integration of EMG-based adaptive actuators successfully created a closed-loop rehabilitation system capable of providing dynamic movement assistance according to the patient’s physiological conditions. This study contributes to the development of smart rehabilitation engineering based on biomechanics, IoMT, and ergonomic design as a more adaptive, precise, and efficient solution for modern medical rehabilitation.]]>
Copyrights © 2026
