Benjamin Gautier

Heriot-Watt University, University of Edinburgh

Papers

Total Citations

H-Index

About

Benjamin Gautier is a leading researcher in the fields of haptics, human-robot interaction, and surgical training, with a particular focus on quantifying human motor learning through physical interaction. His major contribution lies in developing novel methodologies to measure hand-impedance—the dynamic stiffness and damping of the human hand—during active laparoscopic training tasks using co-manipulated robotic systems. By instrumenting surgical simulators with physically interactive manipulators, Gautier has pioneered techniques to capture how the human hand’s mechanical properties evolve with practice, providing objective, quantitative biomarkers of skill acquisition. His most cited work (2022, 11 citations) demonstrates that hand-impedance measurements can distinguish between professional surgeons and trainees, offering a pathway to more effective, data-driven training curricula. A subsequent study (2018, 5 citations) further validated these methods, showing that impedance changes correlate with training progression. Gautier’s research bridges robotics, biomechanics, and medical education, with the potential to transform how surgical skills are assessed and taught. His work is foundational for the next generation of adaptive, co-manipulated robotic trainers that respond to a user’s developing expertise.