<![CDATA[This research aims to develop and evaluate Smart Medical Mechanical Systems based on the integration of mechanical engineering, medical sensor engineering, embedded systems, and the Internet of Medical Things (IoMT) to support real-time rehabilitation monitoring. The research uses a Research and Development (R&D) approach with stages of needs analysis, mechanical design, medical sensor integration, embedded system development, laboratory testing, and initial clinical validation. The research subjects involved 42 participants consisting of post-stroke rehabilitation patients, mechanical engineers, biomedical engineers, and rehabilitation doctors. The research instruments include Electromyography (EMG) sensors, Inertial Measurement Units (IMU), load cells, motion capture, usability testing, and a cloud-based rehabilitation monitoring system. The research results show that the system successfully performed real-time monitoring of patients' biomechanical and physiological parameters with a sensor accuracy rate of 94.2%, a 28% increase in movement efficiency, and a 31% increase in user comfort. The system also supports more objective rehabilitation evaluations thru a cloud-based monitoring dashboard. In addition, the ergonomic mechanical design and multimodal sensing integration have proven to enhance the quality of human-rehabilitation device interaction. This research concludes that the integration of smart medical engineering and IoMT can enhance the effectiveness of modern rehabilitation and support the development of data-driven rehabilitation within the smart healthcare ecosystem. This research also contributes to the development of smarter rehabilitation systems that are more adaptive, personalized, and integrated for both clinical rehabilitation and telemedicine.]]>
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