KielMAT: Kiel Motion Analysis Toolbox - An Open-SourcePython Toolbox for Analyzing Neurological Motion Data from VariousRecording Modalities

Digital health technologies enable objective assessment of human mobility in everyday life and are increasingly used in neuroscience and biomechanics. However, transparent, accessible, and open-source software solutions for analyzing motion data from wearable sensors remain limited. The Kiel Motion Analysis Toolbox (KielMAT) is an open-source Python toolbox designed for processing and analyzing neurological motion data acquired from various recording modalities. KielMAT provides validated algorithms for gait sequence detection, initial contact detection, and physical activity monitoring, with additional modules for postural transitions and turning currently under development. The toolbox supports data from inertial measurement units worn at different body locations, such as the lower back or wrist, and follows open-science principles, including compatibility with the Motion-BIDS data standard to promote reproducibility and interoperability. KielMAT features a modular and extensible architecture, enabling straightforward integration of new algorithms developed by the research community. Comprehensive documentation and practical examples facilitate usability for both researchers and clinicians. By providing free, transparent, and clinically relevant tools for motion analysis, KielMAT aims to support digital mobility assessment, foster reproducible research, and accelerate the adoption of wearable-based outcome measures in clinical and research settings.

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  • (Software)

    KielMAT

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