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Basic scripts for worklab devices

Project description

Worklab: a wheelchair biomechanics mini-package

Essential data analysis and (pre-)processing scripts used in my project researching the Lode Esseda wheelchair ergometer in the worklab at the University Medical Centre Groningen. Includes all basic io and calculations for the equipment in the worklab, which means:

  • Measurement wheel (Optipush and SMARTwheel) and ergometer (Esseda) data processing
  • Push-by-push analysis
  • Spirometer (COSMED) data processing
  • IMU (NGIMU) data processing
  • Kinamatics (Optotrak) data processing
  • more(?)


This is an attempt to make analysis of wheelchair biomechanics data more accessible and transparent. Previously all analyses were performed with commercial software that is not available to everyone, especially to people not associated with a university. Having the analysis in Python makes it accessible and more readable (hopefully) for everyone. By sharing the code I hope to be transparent and to reduce the amount of times this code has to be written by other people.

Target audience

People working in our lab that want to work with data from any of our instruments. It can, of course, also be used by other people, provided that you have similar equipment. Most of the time you will only need one or two functions which you can just take from the source code or you can just install the package as it has very little overhead anyways and only uses packages that you probably already have installed. Also have a look at the examples.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.


You need a valid version of Python 3.6+ (because f-strings). This project has a bunch of dependencies for reasons so you will also need the scipy ecosystem , which you probably already have.


Option 1: download the package from this page, and run:

python install

Option 2: installing with pip is even easier:

pip install worklab

Option 3: don’t install it and just include the scripts in your working directory (why though?).

To verify if everything works simply try to import worklab:

import worklab as wl

That’s it.


Core files:
  • Provides functions for reading and writing data, use load to infer filetype and automatically read it. If you use a different naming scheme you can always call the specific load functions.
  • Contains all essentials for measurement wheel and ergometer data. You only need the top-level function auto_process for most use-cases.
  • Contains kinematics and movement related functions for NGIMU and some functions for 3D kinematics.
  • Contains physiological calculations, which for now is basically nothing as the spirometer does everything for you. Might include EMG and the likes later though.
  • Contains some basic plotting functionalities for plots that become repetitive, needs some TLC to become really useful.
  • Contains all functions that are useful for more than one application (e.g. filtering and interpolation).

The return of a function is a Pandas DataFrame in 9/10 cases. This means that you can also use all Pandas goodness.


You can find some Jupyter Notebook examples here.

Projects using same code

  • Viewer (built with PyQt) - source unfortunately was lost when my laptop was stolen
  • Coast-down analyzer (built with PySide 2)

Reporting errors

If you find an error or mistake, which entirely possible, please contact me or submit an issue through this page.



If you want to refer to this package please use this DOI: 10.5281/zenodo.3268671, or cite: Klerk. (2019, July 4). Worklab: a wheelchair biomechanics mini-package (Version 1.0.0). Zenodo.


  • Thanks to R.J.K. Vegter for providing information on the Optipush and SMARTwheel systems.
  • Thanks to R.M.A. van der Slikke for providing information on skid correction.
  • Thanks to the people at Umaco for answering my questions however dumb they may be.


  • Vegter, R. J., Lamoth, C. J., De Groot, S., Veeger, D. H., & Van der Woude, L. H. (2013). Variability in bimanual wheelchair propulsion: consistency of two instrumented wheels during handrim wheelchair propulsion on a motor driven treadmill. Journal of neuroengineering and rehabilitation, 10(1), 9.
  • Van der Slikke, R. M. A., Berger, M. A. M., Bregman, D. J. J., & Veeger, H. E. J. (2015). Wheel skid correction is a prerequisite to reliably measure wheelchair sports kinematics based on inertial sensors. Procedia Engineering, 112, 207-212.
  • van der Slikke, R., Berger, M., Bregman, D., & Veeger, D. (2016). Push characteristics in wheelchair court sport sprinting. Procedia engineering, 147, 730-734.

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