accelerometer 7.0.1

A package to extract meaningful health information from large accelerometer datasets e.g. how much time individuals spend in sleep, sedentary behaviour, walking and moderate intensity physical activity

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

We recommend using Anaconda:

1. Download & install Miniconda (light-weight version of Anaconda).
2. (Windows) Once installed, launch the Anaconda Prompt.
3. Create a virtual environment:

   $ conda create -n accelerometer python=3.9 openjdk pip
   

   This creates a virtual environment called accelerometer with Python version 3.9, OpenJDK, and Pip.
4. Activate the environment:

   $ conda activate accelerometer
   

   You should now see (accelerometer) written in front of your prompt.
5. Install accelerometer:

   $ 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):

$ accProcess data/sample.cwa.gz

 <output written to data/sample-outputSummary.json>
 <time series output written to data/sample-timeSeries.csv.gz>

Movement statistics will be stored in a JSON file:

{
    "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:

$ 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:

$ 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.

Contributors Graph