By Liam Beguhn, Rosaha Cho, Alexander Tollman, Patrick Walsh
Initial Python scripted module for analyzing gait from a large dataset from Benchmark Datasets for Bilateral Lower-Limb Neuromechanical Signals from Wearable Sensors during Unassisted Locomotion in Able-Bodied Individuals.
If curious about the exacts of the data and the study, the link to the study is available here.
Make sure you have Docker installed before attempting to recreate this code. It is required to build the containers and run the files.
For Linux and MacOS, you may have to install ZeroMQ separately (Windows Users please use WSL and follow the same instructions). Follow the instructions to install.
Once Docker and ZeroMQ are installed, make sure that you download this .zip file containing Raw and Processed leg data, take out one of the .csv files from the Raw data section, and add to the assets/ folder in the repository.
Once the file has been added, change the name to leg_data.csv and you have everything properly installed and ready to go.
For usage, simply type:
docker compose up; docker compose downto execute.
Once the application has run its course, or you are done watching the application, hit Ctrl+C on your keyboard. The containers will stop running and will remove themselves from your computer.
Note: In case you don't see the application, and you receive some information that says,
Authorization required, but no authorization protocol specified, then look at this StackOverflow problem and it should yield your solution.