https://github.com/pfizer-opensource/scikit-digital-health
Python package for the processing and analysis of Inertial Measurement Unit Data
https://github.com/pfizer-opensource/scikit-digital-health
actigraphy imu-sensor python sensors wearables
Last synced: 3 months ago
JSON representation
Python package for the processing and analysis of Inertial Measurement Unit Data
- Host: GitHub
- URL: https://github.com/pfizer-opensource/scikit-digital-health
- Owner: pfizer-opensource
- License: mit
- Created: 2020-05-15T12:52:41.000Z (about 6 years ago)
- Default Branch: main
- Last Pushed: 2026-04-08T17:29:46.000Z (3 months ago)
- Last Synced: 2026-04-08T18:35:52.238Z (3 months ago)
- Topics: actigraphy, imu-sensor, python, sensors, wearables
- Language: Python
- Homepage: https://scikit-digital-health.readthedocs.io/en/latest/index.html
- Size: 33.1 MB
- Stars: 96
- Watchers: 8
- Forks: 34
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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/PfizerRD/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`.
```shell
conda install scikit-digital-health -c conda-forge
```
or
```shell
pip install scikit-digital-health
```
> [!WARNING]
> Windows pre-built wheels are provided as-is, with limited/no testing on changes made to compile extensions for Windows.
> [!NOTE]
> Windows users may need to install an additional requirement: Microsoft Visual C++ redistributable >14.0. The 2015 version can be found here: https://www.microsoft.com/en-us/download/details.aspx?id=53587
### 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](examples/skdh_tutorial.ipynb)
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.