Python library for digital health measurement
https://github.com/bklynhlth/openwillis
OpenWillis was developed by Brooklyn Health to establish standardized methods in digital phenotyping and make them open and accessible to the scientific community.
It is freely available for non-commercial use (see license).
This website serves as a wiki. It contains a library of resources for OpenWillis users, including installation instructions, feature documentation, how-to guides, and guidelines for researchers.
To stay informed about new features, upcoming meetups, and other updates, join our mailing list. If you’d like to collaborate with our team or have general questions, you can get in touch.
Please always use the following reference when reporting work that has used OpenWillis:
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Worthington, M., Efstathiadis, G., Yadav, V., & Abbas, A. (2024). 172. OpenWillis: An Open-Source Python Library for Digital Health Measurement. Biological Psychiatry, 95(10), S169-S170.
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Detailed setup and installation instructions are provided. This includes a brief tutorial on using OpenWillis in a Jupyter notebook environment.
We created an interactive notebook to get a feel for working with OpenWillis using some sample data. This page provides instructions on how to access this demo.
A database of all OpenWillis functions is provided below. It can be filtered by OpenWillis release and sub-package. Each function’s page has information on how to use the function, a description of the methods, its input and output parameters, and anything else there is to know about it.