Papers

8

Total Citations

206

H-Index

5

About

Anirban Chowdhury is a leading researcher at the intersection of neural engineering, rehabilitation robotics, and brain-computer interfaces (BCIs). His work focuses on developing intelligent, adaptive systems to restore motor function in individuals with neurological impairments, particularly post-stroke hemiparesis. Chowdhury’s major contributions include pioneering EEG-EMG correlation-based BCIs for hand orthosis control (95 citations) and demonstrating that brain-machine interface-driven robot-assisted therapy can improve upper-limb recovery by modulating beta-band cortical networks (42 citations). He has also advanced rehabilitation by designing underactuated hand exoskeletons with impedance adaptation for progressive challenge adjustment (35 citations) and exploring corticomuscular co-activation as both a BCI driver and a biomarker for motor recovery monitoring (19 citations). Beyond upper-limb rehabilitation, his work extends to biologically inspired earthworm-like modular robots for locomotion and 3D object localization for activities of daily living. More recently, Chowdhury has applied machine learning to classify pupil diameter during human-computer interaction, aiming to adapt systems to users’ cognitive load. His research is notable for its translational focus, bridging fundamental neurophysiological insights with practical robotic and BCI technologies to enhance functional recovery and quality of life for people with severe disabilities.

Research Focus

Key Achievements

5
H-Index
8
Papers
206
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation
95 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Indian Institute of Technology Kanpur, University of Essex, University of Ulster

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago