Ahmed Alotaibi
Papers
9
Total Citations
102
H-Index
5
About
Dr. Ahmed Alotaibi is at the forefront of rehabilitation robotics, pioneering intelligent control systems that restore mobility and independence to individuals with disabilities. His research masterfully integrates advanced control theory, adaptive neural networks, and fuzzy logic to create robust, fixed-time tracking controllers for exoskeleton wheelchair systems. His most influential work, a fuzzy-based fixed-time nonsingular tracker for upper-limb exoskeletons (30 citations), demonstrates his ability to solve complex position-tracking challenges under external disturbances. Dr. Alotaibi’s contributions extend beyond control algorithms into sensor innovation, as evidenced by his development of a flexible 3D force sensor based on polymer nanocomposites for soft robotics and medical applications (20 citations). His recent AI-driven hybrid rehabilitation system, which synergizes robotics with EMG-guided electrical stimulation for stroke recovery, represents a transformative step toward personalized, adaptive therapy. With a growing portfolio spanning fault-tolerant control, hybrid brain-machine interfaces, and model-free deep learning approaches, Dr. Alotaibi is shaping the next generation of assistive technologies. His work not only advances theoretical frontiers in nonlinear control but also delivers tangible solutions that improve quality of life for disabled individuals worldwide.
Research Focus
Key Achievements
Top Papers
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