Seedahmed S. Mahmoud
Papers
2
Total Citations
20
H-Index
2
About
Seedahmed S. Mahmoud is a pioneering researcher at the intersection of neural engineering and neurorehabilitation, whose work focuses on integrating brain-computer interfaces (BCIs) into stroke recovery. His primary research areas include error-related potentials (ErrPs), robot-assisted rehabilitation, and closed-loop brain-machine systems. Mahmoud’s major contribution lies in demonstrating that ErrPs—brain signals triggered by perceived errors—can be reliably detected during upper-limb rehabilitation exercises in stroke patients. His landmark 2021 paper, "Classification of error-related potentials evoked during stroke rehabilitation training" (17 citations), established a foundational method for decoding these neural signals in clinical contexts. Building on this, his 2022 proof-of-concept study (3 citations) introduced an ErrP-based robotic rehabilitation system that actively incorporates the patient’s brain into the control loop, moving beyond conventional fixed-program approaches. This work represents a paradigm shift toward "assist-as-needed" therapy, where the system adapts in real-time to the user’s neural feedback. Mahmoud’s research has significant implications for personalized neurorehabilitation, offering a pathway to more engaging and effective stroke therapy by directly leveraging the brain’s own error-monitoring mechanisms.
Research Focus
Key Achievements
Top Papers
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