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Computerized Visual Feedback: An Adjunct to Robotic-Assisted Gait Training

R Banz, MSc, was Research Associate, Spinal Cord Injury Research, Balgrist University Hospital, Zurich, Switzerland, at the time of the study
M Bolliger, PhD, is a postdoctoral fellow at the Spinal Cord Injury Center, Balgrist University Hospital, Zurich, and at the Sensory-Motor Systems Lab, ETH Zurich, Switzerland
G Colombo, PhD, is Chief Executive Officer, Hocoma AG, Volketswil, Switzerland. At the time of the study, he was employed at Balgrist University Hospital, Zurich
V Dietz, MD, is Chair, Department of Paraplegiology, University of Zurich, Zurich, Switzerland, and Director, Spinal Cord Injury Center, Balgrist University Hospital, Zurich
L Lünenburger, PhD, is Head of Software Engineering, Hocoma AG. At the time of the study, he was Deputy Head of Research, Spinal Cord Injury Center, Balgrist University Hospital, Zurich

Address all correspondence to Dr Bolliger at: mbolliger{at}paralab.balgrist.ch

Background and Purpose: Robotic devices for walking rehabilitation allow new possibilities for providing performance-related information to patients during gait training. Based on motor learning principles, augmented feedback during robotic-assisted gait training might improve the rehabilitation process used to regain walking function. This report presents a method to provide visual feedback implemented in a driven gait orthosis (DGO). The purpose of the study was to compare the immediate effect on motor output in subjects during robotic-assisted gait training when they used computerized visual feedback and when they followed verbal instructions of a physical therapist.

Subjects: Twelve people with neurological gait disorders due to incomplete spinal cord injury participated.

Methods: Subjects were instructed to walk within the DGO in 2 different conditions. They were asked to increase their motor output by following the instructions of a therapist and by observing visual feedback. In addition, the subjects’ opinions about using visual feedback were investigated by a questionnaire.

Results: Computerized visual feedback and verbal instructions by the therapist were observed to result in a similar change in motor output in subjects when walking within the DGO. Subjects reported that they were more motivated and concentrated on their movements when using computerized visual feedback compared with when no form of feedback was provided.

Discussion and Conclusion: Computerized visual feedback is a valuable adjunct to robotic-assisted gait training. It represents a relevant tool to increase patients’ motor output, involvement, and motivation during gait training, similar to verbal instructions by a therapist.