Laura Baumgartner
Papers
1
Total Citations
13
H-Index
1
About
Laura Baumgartner is a researcher whose work sits at the intersection of robotics, motor learning, and human-machine interaction. Her key research areas include robot-assisted training, augmented feedback systems, and the biomechanics of complex motor tasks. Her most cited paper, "A virtual trainer concept for robot-assisted human motor learning in rowing" (2011, 13 citations), addresses a fundamental challenge in sports science: the difficulty of simultaneously monitoring multiple physiological and biomechanical variables with high precision. Baumgartner proposed a virtual trainer that delivers concurrent augmented feedback—a method shown to enhance motor learning in complex tasks like rowing, where human trainers often struggle to maintain attention and provide real-time guidance. This work has implications for rehabilitation, sports training, and human-robot collaboration. While her citation count is modest, her contributions are notable for bridging gaps between engineering and human performance, offering a scalable solution for personalized, data-driven coaching. Her research continues to influence the development of intelligent training systems.
Research Focus
Key Achievements
Top Papers
- 1A virtual trainer concept for robot-assisted human motor learning in rowing13 citations · 2011