Mohamad Hajj-Hassan

Papers

Total Citations

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About

Mohamad Hajj-Hassan is a biomedical engineer whose research focuses on the intersection of rehabilitation robotics, biosignal processing, and assistive technologies. His most-cited work, "Pattern recognition of EMG signals: Towards adaptive control of robotic arms" (2016, 7 citations), addresses a critical challenge in prosthetics: restoring dexterous hand function for individuals with limb loss. By harnessing electromyographic (EMG) signals from residual muscles, Hajj-Hassan developed pattern recognition algorithms that enable intuitive, real-time control of robotic arms—a pivotal step toward adaptive, user-responsive prosthetics. This contribution underscores his broader commitment to translating physiological signals into practical, life-changing devices for those with motor disabilities. Beyond this flagship study, his work explores signal processing techniques to improve the robustness and accuracy of myoelectric control systems. While his citation count reflects an emerging career, the direct clinical relevance of his research positions him as a promising voice in neurorehabilitation engineering. For students and researchers, Hajj-Hassan’s work exemplifies how pattern recognition can bridge the gap between human intent and machine action, offering a roadmap for more natural, adaptive human-machine interfaces.