Motor Learning and Robotic Neurorehabilitation

Research group leader

Research focuses

  • Rehabilitation robotics
  • Motor learning
  • Neurorehabilitation for brain injured patient


  • Robotics
  • Virtual reality
  • Error modulating training strategies

Short description

There is increasing interest in using robotic devices to provide rehabilitation therapy following stroke. Robotic guidance is generally used in motor training to reduce performance errors while practicing. However, up to date, the functional gains obtained after robotic rehabilitation are limited. A possible explanation for this limited benefit is the inability of the controllers to adapt to the subjects’ special needs. Research on motor learning has emphasized that movement errors are fundamental signals that drive motor adaptation. Thereby, robotic algorithms that augment errors rather than decrease them have a great potential to provoke better motor learning and neurorehabilitation outcomes, especially in initially more skilled subjects. The aim of our group is to improve robotic neurorehabilitation, developing novel robotic training strategies that augment or reduce movement errors based on subjects’ skill (disability) level, age and characteristics of the trained motor task.

Further information

Research group’s website