(untitled) (Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, 2024)
Elbow paresis, often resulting from brachial plexus injury, presents a significant challenge in the field of rehabilitation. To address this, we have developed a prototype powered orthosis that utilizes non-invasive surface electromyography (EMG) signals from neck muscles, such as the sternocleidomastoid, for intuitive control. This EMG-driven system allows for the precise manipulation of the elbow joint, covering the full physiological range of motion. The prototype’s design integrates an EMG signal processor with an orthosis action operator, creating a seamless interface between human intent and mechanical action. Healthy participants were able to use neck muscle contractions to control elbow rotation effectively, demonstrating the system’s potential for real-world application. The scaled EMG envelope directly influences the orthosis’s rotational actuator, ensuring responsive and accurate control. Through rigorous sensitivity analysis, we optimized the control algorithm by adjusting EMG window lengths, signal filtering, and thresholding parameters. This optimization process ensures that the system can adapt to individual user needs, providing personalized and efficient control. The real-time control achieved with this prototype marks a significant step forward in the development of biomedical rehabilitation devices. It not only offers a practical solution for those affected by elbow paresis but also lays the groundwork for future advancements in neuromechanical interfaces. Our ongoing research aims to refine this technology further, exploring the integration of signal processing algorithms to predict and adapt to user movements, thereby creating a more natural and intuitive user experience. The ultimate goal is to develop a fully functional orthosis that can be readily implemented in clinical settings, providing a non-invasive, effective solution for elbow rehabilitation.