Devicely
Devicely: A Python package for reading, timeshifting and writing sensor data - Published in JOSS (2021)
Science Score: 95.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 6 DOI reference(s) in README and JOSS metadata -
✓Academic publication links
Links to: joss.theoj.org, zenodo.org -
✓Committers with academic emails
1 of 7 committers (14.3%) from academic institutions -
○Institutional organization owner
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✓JOSS paper metadata
Published in Journal of Open Source Software
Repository
Devicely: A Python package for reading, timeshifting and writing sensor data
Basic Info
- Host: GitHub
- Owner: hpi-dhc
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://hpi-dhc.github.io/devicely/
- Size: 9.17 MB
Statistics
- Stars: 16
- Watchers: 4
- Forks: 7
- Open Issues: 3
- Releases: 3
Metadata Files
README.md
Devicely is a Python package for reading, de-identifying and writing data from various health monitoring sensors. With devicely, you can read sensor data and have it easily accessible in dataframes. You can also de-identify data and write them back using their original data format. This makes it convenient to share sensor data with other researchers while mantaining people's privacy.
Installation
PyPi (current release)
Installing devicely is as easy as executing:
pip install devicely
Conda-forge (current release)
To install devicelythrough conda-forge:
conda config --add channels conda-forge
conda config --set channel_priority strict
Once the conda-forge channel has been enabled, devicely can be installed with:
conda install devicely
List all of the versions of devicely available on your platform with:
conda search devicely --channel conda-forge
Locally (development version)
git clone git@github.com:hpi-dhc/devicely.git
cd devicely
pip install .
Sneak Peek
All devices contain the following methods as exemplified through the EmpaticaReader:
empatica_reader = devicely.EmpaticaReader(path_to_empatica_files)
empatica_reader.timeshift()
empatica_reader.write(path_to_write_files)
You can also try this notebook with examples and sample data or check our binder:
Quick Start
To get started quickly, follow our quick-start guide.
Or check the full documentation: https://hpi-dhc.github.io/devicely/
Supported Sensors
Empatica E4 is a wearable device that offers real-time physiological data acquisition such as blood volume pulse, electrodermal activity (EDA), heart rate, interbeat intervals, 3-axis acceleration and skin temperature.
Biovotion Everion is a wearable device used for the continuous monitoring of vital signs. Currently, it measures the following vital signs: heart rate, blood pulse wave, heart rate variability, activity, SPO2, blood perfusion, respiration rate, steps, energy expenditure, skin temperature, EDA / galvanic skin response (GSR), barometric pressure and sleep.
1-lead ECG monitor FarosTM 180 from Bittium is a one channel ECG monitor with sampling frequency up to 1000 Hz and a 3D acceleration sampling up to 100Hz.
Spacelabs (SL 90217) is an oscillometric blood pressure (BP) monitor which can be used to automatically track a person's BP in specificed time intervals.
TimeStamp for Android allows you to record the timestamp of an event at the time it occurs. It also allows you to create specific tags such as "Running" or "Walking" and timestamp those specific activities.
Shimmer Consensys GSR is a device that is used to collect sensor data in real time and it contains sensors such as GSR / EDA, photoplethysmography (PPG), 3-axis accelerometer, 3-axis gyroscope, 3-axis magnetometer & integrated altimeter.
Muse S headband is a consumer grade headband consisting of 4 electrodes electroencephalography (EEG) sensors, 3-axis accelerometer (ACC), gyroscope, and photoplethysmography (PPG) sensors.
How to Contribute
If you want to be part of this mission, please check our documentation on how to contribute here.
Authors
* Ariane Sasso
* Jost Morgenstern
* Felix Musmann
* Bert Arnrich
Contributors
* Arpita Kappattanavar
* Bjarne Pfitzner
* Lin Zhou
* Pascal Hecker
* Philipp Hildebrandt
* Sidratul Moontaha
Citation
Sasso, A., Morgenstern, J., Musmann, F., & Arnrich, B. (2021). Devicely: A Python package for reading, timeshifting and writing sensor data. Journal of Open Source Software, 6(66), 3679. https://doi.org/10.21105/joss.03679
BibTeX
@article{Sasso2021,
doi = {10.21105/joss.03679},
url = {https://doi.org/10.21105/joss.03679},
year = {2021},
publisher = {The Open Journal},
volume = {6},
number = {66},
pages = {3679},
author = {Ariane Sasso and Jost Morgenstern and Felix Musmann and Bert Arnrich},
title = {Devicely: A Python package for reading, timeshifting and writing sensor data},
journal = {Journal of Open Source Software}
}
Owner
- Name: Digital Health Center
- Login: hpi-dhc
- Kind: organization
- Location: Potsdam, Germany
- Website: https://hpi.de/digital-health-center/
- Repositories: 17
- Profile: https://github.com/hpi-dhc
This GitHub organization hosts code for different research projects within the Digital Health Center at the HPI
JOSS Publication
Devicely: A Python package for reading, timeshifting and writing sensor data
Authors
Digital Health Center, Hasso Plattner Institute, University of Potsdam
Digital Health Center, Hasso Plattner Institute, University of Potsdam
Digital Health Center, Hasso Plattner Institute, University of Potsdam
Digital Health Center, Hasso Plattner Institute, University of Potsdam
Editor
Prashant Jha
Tags
Wearables Sensors HealthGitHub Events
Total
Last Year
Committers
Last synced: 6 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| jostmorgenstern | J****n@s****e | 136 |
| Ariane Morassi Sasso | a****o@h****e | 113 |
| Ariane Sasso | a****o@g****m | 58 |
| Jost Morgenstern | j****n@w****e | 5 |
| jostmorgenstern | 4****n | 4 |
| firefly-cpp | i****k@i****u | 2 |
| Harry Freitas da Cruz | h****z@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 25
- Total pull requests: 38
- Average time to close issues: about 2 months
- Average time to close pull requests: 2 days
- Total issue authors: 5
- Total pull request authors: 6
- Average comments per issue: 1.76
- Average comments per pull request: 0.03
- Merged pull requests: 32
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- luciorq (14)
- arianesasso (8)
- firefly-cpp (1)
- agricolab (1)
- jostmorgenstern (1)
Pull Request Authors
- jostmorgenstern (30)
- arianesasso (3)
- firefly-cpp (2)
- QuLogic (2)
- anukaal (1)
- jvm-lab (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
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Total downloads:
- pypi 23 last-month
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Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 3
(may contain duplicates) - Total versions: 11
- Total maintainers: 2
pypi.org: devicely
Devicely: A Python package for reading, timeshifting and writing sensor data.
- Homepage: https://github.com/hpi-dhc/devicely
- Documentation: https://hpi-dhc.github.io/devicely
- License: MIT
-
Latest release: 1.1.1
published over 4 years ago
Rankings
Maintainers (2)
conda-forge.org: devicely
- Homepage: https://github.com/hpi-dhc/devicely
- License: MIT
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Latest release: 1.1.1
published over 4 years ago
Rankings
Dependencies
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- python-dateutil 2.8.2
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- coverage ^5.5 develop
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- importlib-metadata ^1.0
- numpy ^1.21.1
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