Will Hoult

McLaren Honda (United Kingdom), Université Paris-Est Créteil

Papers

Total Citations

H-Index

About

Will Hoult is a rising researcher in the field of rehabilitation robotics, with a primary focus on lower limb exoskeletons (LLEs) and human-robot interaction. His work addresses the critical challenge of achieving seamless synergy between robotic assistive devices and human effort, a key bottleneck in modern rehabilitation engineering. Hoult’s most notable contribution is his pioneering approach to human joint torque modelling, which fuses mechanomyography (MMG) and electromyography (EMG) signals during human-exoskeleton interaction. This work, published in 2021 and garnering 58 citations, provides a robust framework for mapping muscle activity to predict user intent, enabling more intuitive and adaptive robotic assistance. Additionally, Hoult has advanced the application of Model Predictive Control (MPC) for human-centred robotic assistance, tackling the complex problem of optimal “assist-as-needed” (AAN) control strategies. Though his career is still early-stage, his work is already influencing the design of smarter, more responsive exoskeletons for mobility-impaired individuals. Hoult’s research sits at the intersection of biomechanics, control theory, and human-robot collaboration, promising significant impact for rehabilitation and assistive technologies.