Yeganeh M. Marghi

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About

Yeganeh M. Marghi is a researcher at the intersection of neural engineering and rehabilitation robotics, with key contributions in brain-computer interfaces (BCIs) and robotic therapy for motor recovery. Her most cited work, "EEG-guided robotic mirror therapy system for lower limb rehabilitation" (2017, 10 citations), pioneers a novel closed-loop framework that integrates electroencephalography (EEG) signals with robotic mirror therapy to enhance stroke rehabilitation outcomes. By decoding neural intent from EEG and synchronizing it with robotic assistance, Marghi addresses a critical gap in lower limb recovery, where conventional therapies often yield limited results. This work demonstrates her ability to combine real-time neural decoding with adaptive robotic control, offering a personalized, neurofeedback-driven approach to motor retraining. Her research has implications for advancing assistive technologies that leverage the brain’s plasticity, potentially improving quality of life for individuals with motor impairments. With a focus on translating neural signals into actionable rehabilitation strategies, Marghi’s contributions are shaping the future of neurorehabilitation, bridging the gap between neural engineering and clinical practice.