Papers
11
Total Citations
89
H-Index
5
About
Khalid Abidi’s research stands at the intersection of robotics, control systems, and biomedical engineering, with a focus on decoding human intent for advanced human-machine interaction. His work addresses critical challenges in teleoperation, rehabilitation robotics, and physiological signal analysis. A key contribution is his adaptive control framework for teleoperation, which compensates for destabilizing communication delays while preserving force feedback transparency—a fundamental problem in telerobotics (24 citations). Abidi has also pioneered the integration of fuzzy inference systems with long short-term memory networks for electromyography (EMG) signal analysis, enabling more reliable decoding of neuromuscular activity for applications ranging from remote surgery to prosthetic control (21 citations). His recent work extends to real-time edge computing for physiological signal classification, and he has developed an EMG-aided robotic hand for rehabilitation, demonstrating practical proof-of-concept. With publications spanning sliding mode control for robotic fish and autonomous underwater vehicles, Abidi’s interdisciplinary approach bridges theoretical control design with tangible biomedical and robotic applications, making him a notable contributor to the future of assistive and rehabilitative technologies.
Research Focus
Key Achievements
Top Papers
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- 7BIO‐inspired fuzzy inference system—For physiological signal analysis5 citations · 2023
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