Nicolas Gandar

École Polytechnique Fédérale de Lausanne

Papers

1

Total Citations

10

H-Index

1

About

Nicolas Gandar is a researcher at the intersection of rehabilitation robotics, human-robot interaction, and serious gaming, with a focus on post-stroke motor recovery. His most-cited work, "Detecting Compensatory Motions and Providing Informative Feedback During a Tangible Robot Assisted Game for Post-Stroke Rehabilitation" (2021, 10 citations), addresses a critical challenge in gamified therapy: while interactive systems boost patient engagement and motivation, they can inadvertently allow compensatory, or "parasite," movements that undermine rehabilitation efficacy. Gandar’s major contribution lies in developing methods to detect these undesirable motions in real time and deliver informative feedback, ensuring that playful exercises remain therapeutically valid. This work exemplifies his broader effort to design tangible, robot-assisted platforms that balance freedom of movement with clinical rigor. With a growing citation footprint, Gandar’s research is shaping how engineers and clinicians think about feedback-driven rehabilitation, offering a pathway to more effective, patient-centered recovery tools. His achievements highlight a commitment to translating robotic technologies into practical, engaging solutions for neurological rehabilitation.

Research Focus

Key Achievements

1
H-Index
1
Papers
10
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Detecting Compensatory Motions and Providing Informative Feedback During a Tangible Robot Assisted Game for Post-Stroke Rehabilitation
10 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: École Polytechnique Fédérale de Lausanne

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago