4.4 Article

A semi-automated software tool to study treadmill locomotion in the rat: From experiment videos to statistical gait analysis

Journal

JOURNAL OF NEUROSCIENCE METHODS
Volume 190, Issue 2, Pages 279-288

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2010.05.006

Keywords

Video processing; Robust methods; Bootstrap analysis; Gait patterns; Motion tracking

Funding

  1. Canadian Foundation for Innovation
  2. Canadian Institutes for Health Research (CIHR)
  3. Natural Sciences and Engineering Research Council of Canada (NSERC)

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A computer-aided method for the tracking of morphological markers in fluoroscopic images of a rat walking on a treadmill is presented and validated. The markers correspond to bone articulations in a hind leg and are used to define the hip, knee, ankle and metatarsophalangeal joints. The method allows a user to identify, using a computer mouse, about 20% of the marker positions in a video and interpolate their trajectories from frame-to-frame. This results in a seven-fold speed improvement in detecting markers. This also eliminates confusion problems due to legs crossing and blurred images. The video images are corrected for geometric distortions from the X-ray camera, wavelet denoised, to preserve the sharpness of minute bone structures, and contrast enhanced. From those images, the marker positions across video frames are extracted, corrected for rat solid body motions on the treadmill, and used to compute the positional and angular gait patterns. Robust Bootstrap estimates of those gait patterns and their prediction and confidence bands are finally generated. The gait patterns are invaluable tools to study the locomotion of healthy animals or the complex process of locomotion recovery in animals with injuries. The method could, in principle, be adapted to analyze the locomotion of other animals as long as a fluoroscopic imager and a treadmill are available. (C) 2010 Elsevier B.V. All rights reserved.

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