Daniel Geller

Columbia University

Papers

1

Total Citations

56

H-Index

1

About

Daniel Geller is a leading researcher in rehabilitation robotics and neurorehabilitation, with a focus on developing wearable technologies to restore motor function after stroke. His most-cited work, "User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke" (2020, 56 citations), introduces a novel robotic orthosis that is both wearable and fully user-controlled, serving dual roles as a therapeutic tool for hand exercises and an assistive device for daily tasks. This contribution highlights his commitment to user-centered design, empowering patients to actively drive their recovery. Geller’s research bridges engineering and clinical practice, advancing accessible, low-cost solutions for upper-limb rehabilitation. His work has been recognized for its potential to transform post-stroke care by promoting neuroplasticity through functional, task-specific training. With a growing citation impact, Geller is shaping the future of assistive robotics, making him a key figure for students and researchers interested in human-robot interaction and motor recovery.

Research Focus

Key Achievements

1
H-Index
1
Papers
56
Total Citations
56
Avg Citations/Paper
🏆 Most Cited Paper
User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke
56 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Columbia University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago