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README.md

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## Expressive movement analysis toolkit
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*A modern, modular, and accessible Python library for expressive movement analysis — bridging research, health, and the arts*
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[![PyPI version](https://img.shields.io/pypi/v/pyeyesweb.svg)](https://pypi.org/project/pyeyesweb/)
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[![Docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://infomuscp.github.io/PyEyesWeb/)
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[![PyPI version](https://img.shields.io/pypi/v/pyeyesweb.svg)](https://pypi.org/project/pyeyesweb/)
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[![Docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://infomuscp.github.io/PyEyesWeb/)
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[![License](https://img.shields.io/github/license/USERNAME/PyEyesWeb.svg)](LICENSE)
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`PyEyesWeb` is a research toolkit for extracting quantitative features from human movement data.
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sparc, jerk = smoothness(window)
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```
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!!! tip
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For more advanced and complete use cases see the [Documentation](https://infomuscp.github.io/PyEyesWeb/)
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and the [examples](examples) folder.
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> [!TIP]
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> For more advanced and complete use cases see the [Documentation](https://infomuscp.github.io/PyEyesWeb/)
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> and the [examples](examples) folder.
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## Documentation
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4. Submit a pull request to the `main` branch, with a clear description of your changes.
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5. Engage in code reviews and address any feedback provided by maintainers.
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## Citation
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If you use `PyEyesWeb` in your research, please cite it as follows:
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### BibTeX
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```bibtex
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@misc{pyeyesweb2025,
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title = {PyEyesWeb: A Python Toolkit for Expressive Movement Analysis},
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author = {InfoMus Lab – Casa Paganini},
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year = {2025},
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howpublished = {\url{https://github.com/infomuscp/PyEyesWeb}}
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}
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```
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## Authors & Acknowledgments
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`PyEyesWeb` is developed by [**InfoMus Lab – Casa Paganini**](http://www.casapaganini.org/index_eng.php){:target="_blank"}, University of Genoa, as part of the **[Resilence EU Project](https://www.resilence.eu/)**, funded by the European Union’s Horizon programme.

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