Yusuf Uzzama Khan
Papers
2
Total Citations
7
H-Index
2
About
Yusuf Uzzama Khan is a researcher in the field of brain-computer interfaces (BCIs) and non-invasive neural signal processing. His work focuses on decoding human motor intent from electroencephalographic (EEG) signals, with the goal of enabling assistive technologies for individuals with neuromuscular disorders. In his most-cited study, "Detection of wrist movement using EEG signal for brain machine interface" (2013, 5 citations), Khan explored how non-invasive EEG can be used to detect wrist movements, offering a safer alternative to invasive methods like electrocorticography (ECoG). His earlier work, "Elbow movement detection using brain computer interface" (2012, 2 citations), investigated the use of simple time-domain statistical features—such as mean, variance, and skewness—to translate human elbow movement into commands for an artificial actuator. Though his citation counts are modest, Khan’s contributions are notable for advancing the feasibility of non-invasive BCIs, which have the potential to improve quality of life for paralyzed patients. His research underscores a commitment to accessible, low-cost neural interfaces, bridging the gap between laboratory signal processing and real-world prosthetic control.
Research Focus
Key Achievements
Top Papers
- 1Detection of wrist movement using EEG signal for brain machine interface5 citations · 2013
- 2Elbow movement detection using brain computer interface2 citations · 2012