Stephen J. Redmond
Papers
22
Total Citations
1,311
H-Index
12
About
Stephen J. Redmond is a prominent biomedical and robotics engineer whose research sits at the intersection of tactile sensing, dexterous manipulation, and human-machine interfaces. Working across both biological and artificial sensing systems, Redmond has made foundational contributions to our understanding of how touch enables skilled object handling — and how those principles can be replicated in robotic and prosthetic devices. His most cited work, a 2012 review of tactile sensing technologies in biomedical engineering (709 citations), established a comprehensive framework for the field and remains a key reference for researchers worldwide. This was followed by a highly influential 2018 review on tactile sensors for friction estimation and incipient slip detection (222 citations), addressing one of robotics' most persistent challenges: matching the effortless dexterity of the human hand. Central to Redmond's experimental output is the PapillArray tactile sensor, a novel device he developed and validated for detecting incipient slip and estimating friction in real time — work that bridges fundamental neuroscience, exploring how human tactile afferents encode grip safety, with applied engineering for prosthetics and robotic manipulation. His more recent investigations into finger pad biomechanics and deep reinforcement learning for robotic control demonstrate a continuously expanding research vision with meaningful real-world impact.
Research Focus
Key Achievements
Top Papers
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- 6Tactile afferents encode grip safety before slip for different frictions27 citations · 2014
- 7Real-time Friction Estimation for Grip Force Control27 citations · 2021
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- 9Biomechanics of the finger pad in response to torsion18 citations · 2023
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