Implementation of virtual control strategies for natural rehabilitation of arm with visual and force feedback

This source preferred by Venky Dubey

Authors: Dubey, V.N., Klopot, W. and Skupin, P.

Start date: 14 December 2010

Publisher: IEEE

Robotic training following stroke is an emerging rehabilitation technique to facilitate neuromuscular plasticity for regaining functional movements. Most existing training robots follow a defined task-based trajectory in assistive or resistive mode. Whilst this approach may be effective in certain cases it does not allow training of arm or leg in a natural way as the motion is precisely guided by the robot or exoskeleton. The ideal training would be to allow arm/leg follow a trajectory naturally without any augmented support and bring it back when the limb is diverted significantly from the goal. This paper presents implementation of this approach in a virtual environment using a simple force feedback joystick. This will guide the arm within a tunnel of trajectory by providing assistance or resistance depending on location of the arm. The technique can be extended for 3-dimensoional arm movement which can help learn neural plasticity naturally.

This data was imported from DBLP:

Authors: Dubey, V.N., Klopot, W. and Skupin, P.

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5720496

Journal: ROBIO

Pages: 69-74

Publisher: IEEE

ISBN: 978-1-4244-9319-7

DOI: 10.1109/ROBIO.2010.5723305

This data was imported from Scopus:

Authors: Dubey, V.N., Klopot, W. and Skupin, P.

Journal: 2010 IEEE International Conference on Robotics and Biomimetics, ROBIO 2010

Pages: 69-74

ISBN: 9781424493173

DOI: 10.1109/ROBIO.2010.5723305

Robotic training following stroke is an emerging rehabilitation technique to facilitate neuromuscular plasticity for regaining functional movements. Most existing training robots follow a defined task-based trajectory in assistive or resistive mode. Whilst this approach may be effective in certain cases it does not allow training of arm or leg in a natural way as the motion is precisely guided by the robot or exoskeleton. The ideal training would be to allow arm/leg follow a trajectory naturally without any augmented support and bring it back when the limb is diverted significantly from the goal. This paper presents implementation of this approach in a virtual environment using a simple force feedback joystick. This will guide the arm within a tunnel of trajectory by providing assistance or resistance depending on location of the arm. The technique can be extended for 3-dimensoional arm movement which can help learn neural plasticity naturally. © 2010 IEEE.

The data on this page was last updated at 04:42 on September 22, 2017.