Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders.

Journal: Journal of neuroengineering and rehabilitation
Published Date:

Abstract

BACKGROUND: In clinical practice, therapists choose the amount of assistance for robot-assisted training. This can result in outcomes that are influenced by subjective decisions and tuning of training parameters can be time-consuming. Therefore, various algorithms to automatically tune the assistance have been developed. However, the assistance applied by these algorithms has not been directly compared to manually-tuned assistance yet. In this study, we focused on subtask-based assistance and compared automatically-tuned (AT) robotic assistance with manually-tuned (MT) robotic assistance.

Authors

  • Simone S Fricke
    Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands. s.s.fricke@utwente.nl.
  • Cristina Bayón
    Centre for Automation and Robotics (CAR), CSIC-UPM, Ctra Campo Real km 0.2 - La Poveda-Arganda del Rey, 28500, Madrid, Spain.
  • Herman van der Kooij
    Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands.
  • Edwin H F van Asseldonk
    Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands.