Toby Dylan Hocking
Papers
1
Total Citations
18
H-Index
1
About
Toby Dylan Hocking is a leading researcher at the intersection of machine learning, robotics, and rehabilitation engineering. His work focuses on developing predictive models and algorithms that enhance human-robot interaction, particularly for assistive devices like robotic exoskeletons. One of his most impactful contributions is the application of supervised machine learning to predict neuromuscular engagement during gait training with a robotic ankle exoskeleton, a study that has garnered 18 citations since 2023. This work addresses a critical challenge in rehabilitation: ensuring that patients achieve appropriate muscle recruitment for effective therapy. Hocking’s research bridges computational methods and clinical application, aiming to improve the efficacy of robotic interventions for individuals with motor impairments. His notable achievements include pioneering the use of machine learning to anticipate neuromuscular responses in real-time, a step toward personalized rehabilitation. By combining rigorous data-driven approaches with practical biomechanical insights, Hocking is advancing the field of assistive robotics, making him a key figure for students and researchers interested in the future of human-centered robotics and rehabilitation technology.
Research Focus
Key Achievements
Top Papers
- 1