Mobile Visual Feedback for Gait Training

Abstract

The proposed project aims to expand on a promising line of research on gait retraining and optimization. We have previously developed and tested a system and method of providing real-time mobile visual feedback on gait quality, based on kinetic data that is collected by wearable sensors. A critical advantage of this approach is that users receive pertinent and timely information on their gait pattern and that they see the immediate results of any gait adaptations. Initial applications for this were in people with lower limb prostheses. However the potential of this technology extends to other and larger populations as well.

                

Project Lead

Goeran Fiedler, PhD
Co-Project Lead
School of Health and Rehabilitation Sciences

Krista Kutina, DPT, PhD candidate
Co-Project Lead
Rehabilitation Science and Technology

Select Collaborators

William Clark, PhD 
Team Member
Mechanical Engineering and Materials Science

April Chambers, PhD
Team Member
Bioengineering

Jarad Prinkey 
Team Member
Bioengineering

Jon Pearlman, PhD 
Team Member
Rehabilitation Science and Technology