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

Abstract

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.