Mohamed Zine-El-Abidine Amrani
Papers
1
Total Citations
7
H-Index
1
About
Mohamed Zine-El-Abidine Amrani is a researcher whose work sits at the intersection of biomedical engineering, rehabilitation robotics, and intelligent control systems. His primary research focus is on developing assistive technologies that restore motor function, with a particular emphasis on myoelectric control—using electromyography (EMG) signals to command robotic devices. His most cited paper, "Artificial neural networks based myoelectric control system for automatic assistance in hand rehabilitation" (2017, 7 citations), demonstrates a novel approach to automating tendon gliding exercises. By integrating artificial neural networks with EMG signal processing, Amrani created a system that interprets user intent to drive a rehabilitation robot, offering a more adaptive and responsive therapy for hand recovery. This work is notable for bridging machine learning with practical clinical applications, aiming to reduce therapist burden and improve patient outcomes. Though early in his career, his contributions highlight a promising trajectory in human-machine interaction for rehabilitation, with potential to impact stroke and injury recovery protocols.
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Top Papers
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