Scikit Digital Health (SKDH) is a Python package with methods for ingesting and analyzing wearable inertial sensor data.
- Documentation: https://scikit-digital-health.readthedocs.io/en/latest/
- Bug reports: https://github.com/pfizer-opensource/scikit-digital-health/issues
- Contributing: https://scikit-digital-health.readthedocs.io/en/latest/src/dev/contributing.html
SKDH provides the following:
- Methods for ingesting data from binary file formats (ie Axivity, GeneActiv)
- Preprocessing of accelerometer data
- Common time-series signal features
- Common time-series/inertial data analysis functions
- Inertial data analysis algorithms (ie gait, sit-to-stand, sleep, activity)
Availability
SKDH is available on both conda-forge and PyPI.
conda install scikit-digital-health -c conda-forge
or
pip install scikit-digital-health
Build Requirements
As of 0.9.15, Scikit Digital Health is built using Meson.
Examples
An example notebook can be found in the examples folder: SKDH tutorial along with some sample data. The tutorial walks through running individual modules in SKDH, then building up a pipeline, and finally creating a new module.
Citation
If you use SKDH in your research, please include the following citation:
[1] L. Adamowicz, Y. Christakis, M. D. Czech, and T. Adamusiak, “SciKit Digital Health: Python Package for Streamlined Wearable Inertial Sensor Data Processing,” JMIR mHealth and uHealth, vol. 10, no. 4, p. e36762, Apr. 2022, doi: 10.2196/36762.
1 maintainer
Metadata
1 maintainer
Release files for scikit-digital-health 0.17.18
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scikit_digital_health-0.17.18.tar.gz | 8.4 MB | Details |
Built distributions (wheels)
Total release size: 46.6 MB
Release files / scikit_digital_health-0.17.18.tar.gz
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Release files / scikit_digital_health-0.17.18-cp314-cp314t-win_amd64.whl
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Release files / scikit_digital_health-0.17.18-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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Release files / scikit_digital_health-0.17.18-cp314-cp314t-macosx_26_0_arm64.whl
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