Python general purpose human motion inertial data processing package.
Project description
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.
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.
Citation
If you use SKDH in your research, please include the following citation:
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.
Project details
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