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: 1 day ago
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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 (over 4 years ago)
• Default Branch: main
• Last Pushed: 2024-08-30T21:39:09.000Z (27 days ago)
• Last Synced: 2024-08-30T21:47:56.844Z (27 days ago)
• Topics: actigraphy, imu-sensor, python, sensors, wearables
• Language: Python
• Homepage: https://scikit-digital-health.readthedocs.io/en/latest/index.html
• Size: 31.3 MB
• Stars: 60
• Watchers: 12
• Forks: 20
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
![skdh_badge](https://github.com/PfizerRD/scikit-digital-health/workflows/skdh/badge.svg)

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.

### 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.