Shubhanshu Sharma
Papers
2
Total Citations
5
H-Index
2
About
Shubhanshu Sharma is pioneering a novel approach to automatic terrain recognition by integrating electrical impedance measurement directly into footwear. His research sits at the intersection of biomedical engineering, assistive technology, and robotics, addressing a critical sensing challenge: how to reliably classify walking surfaces in real-time. Sharma’s major contribution is the development of shoes with embedded electrodes that measure ground impedance underfoot, enabling automatic pathway classification. This innovation has profound implications for safe navigation among the visually impaired, lower-limb amputees, and diabetic patients with neuropathy, as well as for autonomous robots and vehicles. His foundational 2022 feasibility study (3 citations) established the method, while his 2024 paper (2 citations) advanced the system toward practical application. Though early in his career, Sharma’s work represents a creative fusion of wearable electronics and machine learning, offering a low-cost, intuitive solution to a problem that has resisted simple sensor-based approaches. By turning an ordinary shoe into a smart sensing platform, he is helping to close the gap between human mobility needs and autonomous navigation systems.
Research Focus
Key Achievements
Top Papers
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- 2