Connal de Souza

University of Toronto

Papers

1

Total Citations

7

H-Index

1

About

Connal de Souza is a researcher at the forefront of rehabilitation robotics, specializing in the design and control of lower-body exoskeletons for stroke recovery. His work bridges the critical gap between simulation and real-world application, enabling more seamless customization of gait patterns for patients. His most-cited paper, "A Framework for Mapping and Controlling Exoskeleton Gait Patterns in Both Simulation and Real-World" (2020), introduces an integrated approach that allows for rapid, on-the-fly adjustments to robotic assistance—a key step toward personalized rehabilitation. With 7 citations, this work has already influenced discussions on streamlining exoskeleton development. De Souza’s contributions lie at the intersection of biomechanics, control systems, and human-robot interaction, aiming to make robotic therapy more accessible and effective. His research not only advances technical methodologies but also holds promise for improving mobility and quality of life for individuals with neurological impairments. As the field of wearable robotics grows, de Souza’s work offers a practical pathway from lab-based simulations to real-world clinical impact.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
A Framework for Mapping and Controlling Exoskeleton Gait Patterns in Both Simulation and Real-World
7 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Toronto

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago