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Scikit Digital Health (SKDH) is a Python package with methods for ingesting and analyzing wearable inertial sensor data.

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)

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:

  1. 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.

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Python package for the processing and analysis of Inertial Measurement Unit Data

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  • Python 72.3%
  • Fortran 14.9%
  • C 12.1%
  • Meson 0.7%