Nikunj Bhagat
Papers
6
Total Citations
126
H-Index
4
About
Nikunj Bhagat is a leading researcher at the intersection of neural engineering and rehabilitation robotics, whose work is redefining motor recovery after stroke. His primary research focuses on developing brain-machine interfaces (BMI) that decode movement intent from scalp EEG to drive robotic exoskeletons, such as the MAHI-Exo II. Bhagat’s key contributions include demonstrating that BMI-enabled robotic training can promote cortical plasticity and improve upper-limb function in chronic stroke survivors, with his most cited work (70 citations) quantifying neural activity modulations alongside clinical outcomes. He has also pioneered methods for detecting movement intent in real-time, achieving 27 citations for a foundational study on a novel rehabilitation system. Beyond stroke rehabilitation, Bhagat has explored tremor cancellation for microsurgery, showcasing his versatility. His clinical trials, including a multi-year study with preliminary results cited 19 times, provide compelling evidence for integrating neural intent detection into robotic therapy. Through this work, Bhagat is advancing a new paradigm where the brain’s own signals guide recovery, offering hope for restoring quality of life after neurological injury.
Research Focus
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Top Papers
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