Papers
1
Total Citations
28
H-Index
1
About
Riaz Ahmad is a pioneering researcher at the intersection of neuroergonomics, assistive robotics, and brain-machine interfaces (BMI). His work centers on developing intelligent systems that bridge human cognitive states with robotic assistance, particularly for individuals with motor impairments. In his highly cited 2021 study, Ahmad demonstrated how mental workload (MWL) monitoring using functional near-infrared spectroscopy (fNIRS) can optimize motor training with soft exoskeletons—a breakthrough that integrates neurofeedback with assistive technologies to enhance rehabilitation outcomes. By quantifying neural correlates of cognitive effort during physical tasks, his research enables adaptive robotic prosthetics that respond to a user’s real-time mental state, improving safety and efficacy in hemiplegic patient care. With 28 citations on this seminal work alone, Ahmad’s contributions are shaping the future of neuroergonomic design and closed-loop BMI systems. His interdisciplinary approach—merging neuroscience, engineering, and human factors—positions him as a key innovator in assistive robotics, offering transformative pathways for restoring motor function and independence.
Research Focus
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