Daniel Clos Costa

Universitat Politècnica de Catalunya

Papers

5

Total Citations

73

H-Index

5

About

Daniel Clos Costa is a robotics engineer and researcher specializing in assistive wearable technologies, with a particular focus on robotic exoskeletons for gait rehabilitation in individuals with spinal cord injury (SCI). His work spans the full development pipeline — from mechanical design and actuation to control strategies and experimental validation — making him a well-rounded contributor to the field of rehabilitation robotics. His most influential contribution, "Design, Control, and Pilot Study of a Lightweight and Modular Robotic Exoskeleton for Walking Assistance After Spinal Cord Injury" (2019, 40 citations), demonstrates his commitment to creating practical, patient-centered solutions that balance performance with wearability. Alongside this, his ABLE exoskeleton project and earlier low-cost orthosis designs reflect a consistent drive to make assistive robotic technology more accessible beyond clinical settings. His investigation into series elastic actuator optimization further highlights his depth in the biomechanics-engineering interface. More recently, his work on objective evaluation methodologies for human-exoskeleton interaction using robotic dummy legs signals a maturing research agenda focused on rigorous, ethically sound assessment frameworks. With cumulative citations exceeding 70, Costa's research is establishing meaningful ground in making robotic walking assistance safer, more affordable, and more widely available to those who need it most.

Research Focus

Key Achievements

5
H-Index
5
Papers
73
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Design, Control, and Pilot Study of a Lightweight and Modular Robotic Exoskeleton for Walking Assistance After Spinal Cord Injury
40 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Universitat Politècnica de Catalunya

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago