Yousef Alshahrani
Papers
3
Total Citations
20
H-Index
3
About
Yousef Alshahrani is a researcher at the forefront of robotic rehabilitation and assistive technology, specializing in the real-time control of upper-limb exoskeletons using electromyography (EMG) signals and machine learning. His work directly addresses the challenge of improving performance in robotic assistive devices for neurologically impaired patients and surgical applications. Alshahrani’s major contributions include developing a novel upper extremity exoskeleton and pioneering real-time, multiple-channel shoulder EMG processing for motion control. Notably, he has advanced beyond traditional RMS-based algorithms by integrating artificial neural networks (ANN) for online, rather than off-line, signal analysis—a critical step toward practical, responsive assistive robots. His most cited work, "A Real-Time EMG-Based Fixed-Bandwidth Frequency-Domain Embedded System for Robotic Hand" (2022, 10 citations), demonstrates a high-impact approach to embedded system design for volitional control. With additional publications validating exoskeleton performance using joint ROM signals, Alshahrani’s research is shaping the future of intuitive, machine-learning-driven rehabilitation and assistive robotics.
Research Focus
Key Achievements
Top Papers
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