biobankaccelerometeranalysis
Extracting meaningful health information from large accelerometer datasets
Science Score: 77.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
✓Committers with academic emails
10 of 25 committers (40.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (14.5%) to scientific vocabulary
Keywords
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Repository
Extracting meaningful health information from large accelerometer datasets
Basic Info
- Host: GitHub
- Owner: OxWearables
- License: other
- Language: Python
- Default Branch: master
- Homepage: https://biobankaccanalysis.readthedocs.io/en/latest/index.html
- Size: 25.4 MB
Statistics
- Stars: 216
- Watchers: 22
- Forks: 68
- Open Issues: 24
- Releases: 40
Topics
Metadata Files
README.md
A tool to extract meaningful health information from large accelerometer datasets. The software generates time-series and summary metrics useful for answering key questions such as how much time is spent in sleep, sedentary behaviour, or doing physical activity.
Install
Minimum requirements: Python 3.7 to 3.10, Java 8 (1.8)
The following instructions make use of Anaconda to meet the minimum requirements:
- Download & install Miniconda (light-weight version of Anaconda).
- (Windows) Once installed, launch the Anaconda Prompt.
- Create a virtual environment:
console $ conda create -n accelerometer python=3.9 openjdk pipThis creates a virtual environment calledaccelerometerwith Python version 3.9, OpenJDK, and Pip. - Activate the environment:
console $ conda activate accelerometerYou should now see(accelerometer)written in front of your prompt. - Install
accelerometer:console $ pip install accelerometer
You are all set! The next time that you want to use accelerometer, open the Anaconda Prompt and activate the environment (step 4). If you see (accelerometer) in front of your prompt, you are ready to go!
Usage
To extract summary movement statistics from an Axivity file (.cwa):
```console $ accProcess data/sample.cwa.gz
Movement statistics will be stored in a JSON file:
json
{
"file-name": "sample.cwa.gz",
"file-startTime": "2014-05-07 13:29:50",
"file-endTime": "2014-05-13 09:49:50",
"acc-overall-avg(mg)": 32.78149,
"wearTime-overall(days)": 5.8,
"nonWearTime-overall(days)": 0.04,
"quality-goodWearTime": 1
}
See Data Dictionary for the list of output variables.
Actigraph and GENEActiv files are also supported, as well as custom CSV files. See Usage for more details.
To plot the activity profile:
console
$ accPlot data/sample-timeSeries.csv.gz
<output plot written to data/sample-timeSeries-plot.png>
Troubleshooting
Some systems may face issues with Java when running the script. If this is your case, try fixing OpenJDK to version 8:
console
$ conda install -n accelerometer openjdk=8
Under the hood
Interpreted levels of physical activity can vary, as many approaches can be taken to extract summary physical activity information from raw accelerometer data. To minimise error and bias, our tool uses published methods to calibrate, resample, and summarise the accelerometer data.
See Methods for more details.
Citing our work
When using this tool, please consider the works listed in CITATION.md.
Licence
See LICENSE.md.
Acknowledgements
We would like to thank all our code contributors and manuscript co-authors.
Owner
- Name: Oxford Wearables Group
- Login: OxWearables
- Kind: organization
- Location: United Kingdom
- Twitter: OxWearables
- Repositories: 27
- Profile: https://github.com/OxWearables
Citation (CITATION.cff)
cff-version: 1.0.0 message: "If you use this software, please cite it as below." authors: - family-names: "Doherty" given-names: "Aiden" orcid: "https://orcid.org/0000-0003-1840-0451" - family-names: "Chan" given-names: "Shing" orcid: "https://orcid.org/0000-0001-9600-5575" - family-names: "Yuan" given-names: "Hang" orcid: "https://orcid.org/0000-0001-5944-1925" - family-names: "Walmsley" given-names: "Rosemary" title: "accelerometer: A Python Toolkit for Extracting Physical Activity and Behavior Metrics from Wearable Sensor Data" doi: 10.5281/zenodo.14515076 date-released: 2020-06-03 url: "https://github.com/OxWearables/biobankAccelerometerAnalysis"
GitHub Events
Total
- Create event: 12
- Issues event: 10
- Release event: 6
- Watch event: 34
- Delete event: 6
- Member event: 3
- Issue comment event: 5
- Push event: 15
- Pull request event: 16
- Fork event: 6
Last Year
- Create event: 12
- Issues event: 10
- Release event: 6
- Watch event: 34
- Delete event: 6
- Member event: 3
- Issue comment event: 5
- Push event: 15
- Pull request event: 16
- Fork event: 6
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Aiden Doherty MacBookAir | a****y@d****k | 354 |
| Shing Chan | c****m@g****m | 226 |
| Sven Hollowell | s****1@g****m | 74 |
| angerhang | 5****9@q****m | 54 |
| Aiden Doherty | a****y@b****k | 53 |
| R-Walmsley | r****y@g****k | 26 |
| R-Walmsley | 4****y | 10 |
| Xiangnan Dang | d****n@l****m | 8 |
| dependabot[bot] | 4****] | 6 |
| Dan Jackson | d****n@n****k | 5 |
| nhammerla | n****s@b****l | 4 |
| Gert Mertes | h****y@g****e | 3 |
| Shing Chan at BDI | s****c@n****k | 3 |
| Sven Hollowell | S****l | 3 |
| egctong | e****g@g****m | 2 |
| Aiden Doherty | 2 | |
| Hang Yuan | h****y@N****l | 2 |
| Alaina Cockerell | a****l@s****k | 2 |
| Hang Yuan | c****9@r****k | 2 |
| Aiden Doherty | a****d@e****k | 1 |
| Aiden Doherty | a****y@j****k | 1 |
| xiangnan dang | c****9@b****m | 1 |
| Rosemary Walmsley | R****w@n****k | 1 |
| xiangnan dang | c****9@r****m | 1 |
| xiangnan dang | c****9@r****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: over 1 year ago
All Time
- Total issues: 68
- Total pull requests: 63
- Average time to close issues: 7 months
- Average time to close pull requests: about 1 month
- Total issue authors: 23
- Total pull request authors: 8
- Average comments per issue: 2.25
- Average comments per pull request: 1.43
- Merged pull requests: 46
- Bot issues: 0
- Bot pull requests: 7
Past Year
- Issues: 11
- Pull requests: 16
- Average time to close issues: 23 days
- Average time to close pull requests: 16 minutes
- Issue authors: 7
- Pull request authors: 2
- Average comments per issue: 1.91
- Average comments per pull request: 0.06
- Merged pull requests: 13
- Bot issues: 0
- Bot pull requests: 2
Top Authors
Issue Authors
- angerhang (23)
- R-Walmsley (9)
- chanshing (8)
- sehamsick (3)
- smallsr (3)
- mariascedasticity (2)
- tbonewmy (2)
- LeandroCasiraghi (2)
- johnpark12 (2)
- ghammad (2)
- 36310489 (2)
- RitaPeralta (1)
- harkash (1)
- AnnaWojciechowska (1)
- yummyyimao (1)
Pull Request Authors
- chanshing (45)
- angerhang (9)
- R-Walmsley (7)
- dependabot[bot] (7)
- aidendoherty (3)
- gmertes (3)
- econwang (1)
- cosmicnet (1)
Top Labels
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Dependencies
- docutils <0.18
- readthedocs-sphinx-search ==0.1.1
- sphinx ==4.2.0
- sphinx_rtd_theme ==1.0.0
- sphinxcontrib-programoutput ==0.17
- imbalanced-learn ==0.8.1
- joblib ==1.1.0
- matplotlib *
- numpy *
- pandas >=1.2.5
- scikit-learn ==1.0.1
- scipy *
- statsmodels >=0.12.2
- tqdm >=4.59.0
- actions/checkout v2 composite
- actions/setup-java v1 composite
- actions/setup-python v2 composite
- tianhaoz95/mirror-action v1.0.1 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-java v1 composite
- tianhaoz95/mirror-action v1.0.1 composite
- actions/checkout v2 composite
- actions/setup-java v1 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-java v1 composite