Musfira Jilani
Papers
1
Total Citations
2
H-Index
1
About
Musfira Jilani is a researcher at the forefront of Brain-Computer Interface (BCI) technology, with a focused expertise in non-invasive neural signal processing and assistive robotics. Her pioneering work centers on decoding human motor intent from Electroencephalographic (EEG) activity, particularly for upper-limb rehabilitation and prosthetic control. In her highly cited 2012 study, "Elbow movement detection using brain computer interface," Jilani demonstrated a novel approach to translating voluntary elbow movements into commands for an artificial actuator using simple time-domain statistical features—such as mean and variance—extracted from EEG signals. This foundational contribution has garnered 2 citations and laid critical groundwork for low-latency, user-friendly BCI systems. By proving that non-invasive EEG can effectively capture complex motor commands, Jilani’s research directly advances the development of affordable, real-time neuroprosthetics for individuals with motor impairments. Her work stands as a key reference for students and engineers exploring the intersection of neural engineering, machine learning, and human-machine interaction, offering a clear path toward practical, everyday BCI applications.
Research Focus
Key Achievements
Top Papers
- 1Elbow movement detection using brain computer interface2 citations · 2012