Papers
1
Total Citations
7
H-Index
1
About
Darunjeet Bag is a researcher at the forefront of assistive and rehabilitation technologies, with a primary focus on brain-computer interfaces (BCI) and their application in restoring mobility. His most-cited work, "An Automatic Approach to Control Wheelchair Movement for Rehabilitation Using Electroencephalogram" (2022), has garnered 7 citations and represents a significant step toward non-invasive, EEG-based control systems. By harnessing brain signals to direct robotic wheelchairs, Bag’s research directly addresses the needs of individuals with severe motor disabilities, offering a pathway to greater independence and improved quality of life. His contributions lie in developing automatic, real-time decoding algorithms that translate neural activity into precise movement commands, bridging the gap between human intention and machine action. This work not only advances the field of rehabilitation robotics but also demonstrates the practical viability of BCI systems outside laboratory settings. Bag’s research is characterized by its clear translational focus—taking complex neuroengineering concepts and turning them into tangible, life-changing tools. For students and researchers interested in the intersection of neuroscience, signal processing, and assistive technology, Bag’s work exemplifies how cutting-edge BCI research can directly empower those with physical limitations.
Research Focus
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Top Papers
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