Khurram Khalil
Papers
1
Total Citations
28
H-Index
1
About
Khurram Khalil is a pioneering researcher at the intersection of neuroergonomics, brain-machine interfaces (BMI), and assistive robotics. His work centers on decoding mental workload (MWL) through functional near-infrared spectroscopy (fNIRS) to enhance human-robot collaboration, particularly for individuals with motor impairments. In his highly cited 2021 study, Khalil demonstrated how combining motor training with an assistive soft exoskeleton system can leverage real-time fNIRS-based MWL monitoring to create adaptive, closed-loop BMI systems. This research provides a neuroergonomic framework for improving safety and efficacy in assistive technologies, offering new pathways for hemiplegic patients to regain motor function through robotic prosthetics. With 28 citations, this work underscores his impact in advancing non-invasive neural interfaces for rehabilitation. Khalil’s contributions bridge cognitive neuroscience and engineering, positioning him as a key figure in developing intelligent, user-responsive exoskeletons that adapt to the user’s cognitive state. His research holds promise for transforming neurorehabilitation and human-machine interaction, making assistive systems more intuitive and effective for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1