In this project we provide tools for analyzing gait using a video footage from a single camera. Our software is based on machine learning models, in particular on convolutional neural networks.
To train our machine learning models we used a dataset of over 3,000 videos processed with computer vision software finding body landmarks in frames (OpenPose). We provide the source code, dataset of clinical measurements as well as trajectories of body landmarks from OpenPose.

Two key objectives of this SimTK project are:
- providing a toolset for derviation of gait parameters from videos
- providing a dataset allowing further research on gait analysis from videos using data-driven methods.

Try out an online demo at: http://gaitlab.stanford.edu
Download the source code at: https://github.com/stanfordnmbl/mobile-gaitlab