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Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
Published on: March 4, 2018
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Visual Gait Lab: A user-friendly approach to gait analysis.
Robert Fiker1, Linda H Kim2, Leonardo A Molina1
1Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
Journal of Neuroscience Methods
|May 20, 2020
Summary
Visual Gait Lab (VGL) software improves gait analysis by automating paw tracking. This tool, built on DeepLabCut™, offers rapid, unbiased gait metrics and simplifies error correction for researchers.
Area of Science:
- Biomedical Engineering
- Neuroscience Research
- Animal Locomotion Studies
Background:
- Gait analysis is crucial in preclinical neurological studies and locomotion testing.
- Current semi-automated paw detection methods are time-consuming and prone to errors.
- Enhanced paw tracking is needed to improve gait analysis efficiency and accuracy.
Purpose of the Study:
- Introduce Visual Gait Lab (VGL), a novel software for streamlined gait analysis.
- Demonstrate VGL's capability to optimize gait metrics generation and error correction.
- Provide an accessible tool for researchers without programming expertise.
Main Methods:
- Developed VGL, a high-level software utilizing DeepLabCut™ for paw tracking.
- VGL features an intuitive interface and a single executable for easy Windows setup.
- Trained and evaluated VGL using video data of mice walking on a treadmill.
Main Results:
- VGL successfully tracked paw placements to compute gait metrics from video data.
- The software allows for rapid identification and correction of tracking errors.
- Trained network achieved accurate visual tracking for gait analysis.
Conclusions:
- VGL enables rapid and unbiased gait analysis, overcoming limitations of existing methods.
- The software simplifies setup and execution, making advanced gait analysis accessible.
- VGL enhances the overall gait analysis workflow for diverse research applications.
