Parul Sharma

Malaviya National Institute of Technology Jaipur

Papers

Total Citations

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About

Parul Sharma is a researcher at the intersection of artificial intelligence and biomedical engineering, with key contributions in human–machine interaction, assistive robotics, and biosignal processing. Her most cited work, "PC-GNN: Pearson Correlation-Based Graph Neural Network for Recognition of Human Lower Limb Activity Using sEMG Signal" (2023, 26 citations), introduces a novel graph neural network architecture that leverages Pearson correlation to decode surface electromyography (sEMG) signals for lower limb activity recognition. This work has significant implications for the development of intelligent prosthetic limbs and exoskeletons, enabling more natural and responsive human–machine interfaces. Earlier in her career, Sharma contributed to accessible mobility solutions with her paper "Design and development of voice-cum-auto steered robotic wheelchair incorporating reactive fuzzy scheme for anti-collision and auto routing" (2002, 5 citations), which pioneered a hybrid voice and automated control system for wheelchairs, integrating fuzzy logic for collision avoidance and path planning. Her research demonstrates a sustained commitment to applying AI and robotics to improve quality of life, particularly for individuals with mobility impairments.