Visual Gait Lab: A user-friendly approach to gait analysis.,Journal of Neuroscience Methods

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Visual Gait Lab: A user-friendly approach to gait analysis.
Journal of Neuroscience Methods ( IF 2.7 ) Pub Date : 2020-05-16 , DOI: 10.1016/j.jneumeth.2020.108775
Robert Fiker ₁ , Linda H Kim ₂ , Leonardo A Molina ₁ , Taylor Chomiak ₁ , Patrick J Whelan ₃

Affiliation

Background

Gait analysis forms a critical part of many lab workflows, ranging from those interested in preclinical neurological models to others who use locomotion as part of a standard battery of tests. Unfortunately, while paw detection can be semi-automated, it becomes generally a time-consuming process with error corrections. Improvement in paw tracking would aid in better gait analysis performance and experience.

New Method

Here we show the use of Visual Gait Lab (VGL), a high-level software with an intuitive, easy to use interface, that is built on DeepLabCut™. VGL is optimized to generate gait metrics and allows for quick manual error corrections. VGL comes with a single executable, streamlining setup on Windows systems. We demonstrate the use of VGL to analyze gait.

Results

Training and evaluation of VGL were conducted using 200 frames (80/20 train-test split) of video from mice walking on a treadmill. The trained network was then used to visually track paw placements to compute gait metrics. These are processed and presented on the screen where the user can rapidly identify and correct errors.

Comparison with existing methods

Gait analysis remains cumbersome, even with commercial software due to paw detection errors. DeepLabCut™ is an alternative that can improve visual tracking but is not optimized for gait analysis functionality.

Conclusions

VGL allows for gait analysis to be performed in a rapid, unbiased manner, with a set-up that can be easily implemented and executed by those without a background in computer programming.

中文翻译：

视觉步态实验室：一种易于使用的步态分析方法。

背景

步态分析是许多实验室工作流程的重要组成部分，从对临床前神经模型感兴趣的人到将运动作为标准测试系列的一部分的人，都包括在内。不幸的是，虽然爪子检测可以是半自动的，但通常会通过纠错变得很耗时。爪跟踪的改进将有助于获得更好的步态分析性能和体验。

新方法

在这里，我们展示了Visual Gait Lab（VGL）的使用，该软件是基于DeepLabCut™构建的，具有直观，易于使用的界面的高级软件。VGL经过优化，可以生成步态度量标准，并可以快速进行手动错误校正。VGL带有一个可执行文件，可简化Windows系统上的设置。我们演示了使用VGL分析步态的方法。