Tom De Weyer

Hasselt University

Papers

7

Total Citations

184

H-Index

6

About

Tom De Weyer is a rehabilitation technology researcher whose work centers on robot-assisted upper limb rehabilitation for individuals with neurological conditions, particularly multiple sclerosis (MS) and chronic stroke. Over more than a decade of research, he has made significant contributions to understanding how robotic systems, virtual learning environments, and serious games can restore and sustain arm and hand function in people with central nervous system deficits. His most influential work, a 2015 pilot randomized controlled trial (71 citations), demonstrated the feasibility and effects of robot-supported upper limb training in persons with advanced MS, a population rarely studied in intensive exercise research. His subsequent investigation of the I-TRAVLE system (48 citations) provided proof-of-concept evidence for individualized, adaptive robotic training across both MS and stroke populations. Earlier foundational studies explored the clinical relevance of robotic outcome measures and force feedback-enabled training, helping to establish meaningful benchmarks for the field. Beyond conventional robotics, De Weyer has innovated at the intersection of tangible interfaces and game-based therapy, developing systems like Handly to make functional handgrip training more engaging and personalized. His cumulative body of work reflects a consistent commitment to translating rehabilitation technology into clinically meaningful, patient-centered solutions.

Research Focus

Key Achievements

6
H-Index
7
Papers
184
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
Robot-supported upper limb training in a virtual learning environment : a pilot randomized controlled trial in persons with MS
71 citations · 2015
📈 Most Prolific Year: 2011 (2 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Hasselt University

Top Papers

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    Watering the flowers
    10 citations · 2011
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago