Habibulla Khan

Papers

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About

Habibulla Khan is a researcher in biomedical engineering and human-computer interaction, with a focus on assistive technologies. His key research areas include surface electromyography (sEMG) signal processing, neural network-based pattern recognition, and robotic control systems. His most notable contribution is the development of a real-time sEMG-based human-computer interface for robotic wheel control, which uses artificial neural networks to interpret hand gesture signals from up to eight channels of sEMG data. This work, published in 2012, has garnered 2 citations and represents an early effort to create intuitive, non-invasive control systems for mobility aids. Khan’s research addresses critical challenges in assistive robotics, aiming to improve quality of life for individuals with motor impairments. His approach combines signal acquisition, pattern refinement, and real-time implementation, demonstrating a practical pathway from raw biosignals to actionable device commands. While his citation count is modest, his work contributes to the foundational literature on sEMG-driven interfaces, offering insights for future developments in hands-free wheelchair navigation and human-machine collaboration.