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Gaitmap - An Open Ecosystem for IMU-based Human Gait Analysis and Algorithm Benchmarking
  • +11
  • Arne Küderle ,
  • Martin Ullrich ,
  • Nils Roth ,
  • Malte Ollenschläger ,
  • Alzhraa Ibrahim ,
  • Hamid Moradi ,
  • robert richer ,
  • Ann-Kristin Seifer ,
  • Matthias Zürl ,
  • Raul Sîmpetru ,
  • Liv Herzer ,
  • Dominik Prossel ,
  • Felix Kluge ,
  • Bjoern Eskofier
Arne Küderle
Friedrich-Alexander-Universität Erlangen-Nürnberg, Friedrich-Alexander-Universität Erlangen-Nürnberg

Corresponding Author:[email protected]

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Martin Ullrich
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Nils Roth
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Malte Ollenschläger
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Alzhraa Ibrahim
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Hamid Moradi
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robert richer
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Ann-Kristin Seifer
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Matthias Zürl
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Raul Sîmpetru
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Liv Herzer
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Dominik Prossel
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Felix Kluge
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Bjoern Eskofier
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Abstract

Goal: Gait analysis using inertial measurement units (IMUs) has emerged as a promising method for monitoring movement disorders. However, the lack of public data and algorithms hinders method comparison and clinical application development. To address these challenges, this publication introduces the gaitmap ecosystem, a comprehensive set of open source Python packages for gait analysis using foot-worn IMUs. Methods: This initial release includes over 20 state-of-the-art algorithms, enables easy access to seven datasets, and provides eight benchmark challenges with reference implementations. Together with its extensive documentation and tooling, it enables rapid development and validation of new algorithm and provides a foundation for novel clinical applications. Conclusion: The published software projects represent a pioneering effort to establish an open-source ecosystem for IMU-based gait analysis. We believe that this work can democratize the access to high-quality algorithm and serve as a driver for open and reproducible research in the field of human gait analysis and beyond.