Yusuf Uzzaman Khan
Papers
1
Total Citations
5
H-Index
1
About
Yusuf Uzzaman Khan is a researcher whose work centers on non-invasive Brain Machine Interfaces (BMI) and assistive robotics, with a particular focus on restoring motor function for individuals with disabilities. His most cited paper, "Brain Machine Interface for wrist movement using Robotic Arm" (2014), addresses a critical challenge in BMI: enabling precise control of external devices without surgical implants. By studying Electroencephalography (EEG) features, Khan demonstrated how neural signals can be translated into robotic arm movements, offering a safer, more accessible alternative to invasive techniques. This contribution has garnered 5 citations, reflecting its foundational role in non-invasive neuroprosthetics. Khan’s work bridges neuroscience, signal processing, and robotics, aiming to improve quality of life for paralyzed patients. His research highlights the potential of EEG-based systems to decode motor intent, paving the way for affordable, user-friendly assistive technologies. For students and researchers, Khan’s approach underscores the importance of balancing technical innovation with practical, ethical considerations in neuroengineering.
Research Focus
Key Achievements
Top Papers
- 1Brain Machine Interface for wrist movement using Robotic Arm5 citations · 2014