Prithwijit Mukherjee
Papers
2
Total Citations
19
H-Index
2
About
Prithwijit Mukherjee is a rising researcher at the intersection of rehabilitation robotics, biomedical signal processing, and deep learning. His work focuses on developing intelligent, adaptive robotic systems to restore mobility and alleviate chronic pain, particularly for lower limb impairments. Mukherjee’s most cited contribution is a deep learning-based comprehensive robotic system for lower limb rehabilitation (2024, 17 citations), which integrates advanced control architectures to automate and personalize therapy. He further extends this work with an EEG and EMG-induced pain-sensitive learning controller for robotic knee rehabilitation (2025, 2 citations), a novel approach that uses real-time neural and muscular signals to detect pain and adjust robotic assistance accordingly—addressing the growing prevalence of knee pain that severely impacts mobility and quality of life. By combining biosignal processing with adaptive control, Mukherjee aims to reduce reliance on costly, expert-dependent traditional physiotherapy. His research holds promise for making rehabilitation more accessible, responsive, and effective, marking him as an innovator in human-centered medical robotics.
Research Focus
Key Achievements
Top Papers
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