biobankAccelerometerAnalysis
A tool to extract meaningful health information from large accelerometer datasets e.g. how much time individuals spend in sleep, sedentary behaviour, and physical activity.
Usage
To extract a summary of movement (average sample vector magnitude) and (non)wear time from raw Axivity .CWA accelerometer files:python ActivitySummary.py [input_file.CWA] [options]
python ActivitySummary.py sample.cwa
[Click here for a sample .CWA file.] (http://users.fmrib.ox.ac.uk/~adoherty/sample.cwa)
The output will look like:
{
"file-name": "sample.cwa",
"file-startTime": "2014-05-07 13:29:50",
"file-endTime": "2014-05-13 09:50:25",
"pa-overall-avg(mg)": "33.01",
"wearTime-overall(days)": "5.80",
"nonWearTime-overall(days)": "0.04"
}
[Click here for customised usage options on our wiki.] (https://github.com/aidendoherty/biobankAcceleromerAnalysis/wiki/1. Usage)
Installation
Dependancies include: java and python (numpy and pandas).[Click here for detailed information on installing this software on our wiki.] (https://github.com/aidendoherty/biobankAcceleromerAnalysis/wiki/2. Installation)
Under the hood
We are using a combination of published methods to extract meaningful health information from accelerometer data. [Click here for detailed information on the data processing methods on our wiki.] (https://github.com/aidendoherty/biobankAccelerometerAnalysis/wiki/3.-Methods-Overview)![Accelerometer data processing overview] (http://users.fmrib.ox.ac.uk/~adoherty/accProcessingOverviewDec2014.png)