Step counter for wrist-worn accelerometers compatible with the UK Biobank Accelerometer Dataset
Project description
stepcount
A Python package to estimate step counts from accelerometer data.
The algorithm is tuned for wrist-worn AX3 data collected at 100 Hz, matching the UK Biobank Accelerometer Dataset.
Getting started
Install
$ pip install stepcount
Usage
# Process an AX3 file
$ stepcount sample.cwa
# Or a CSV file
$ stepcount sample.csv
# Or an ActiGraph file
$ stepcount sample.gt3x
# Or a GENEActiv file
$ stepcount sample.bin
Output:
Summary
-------
{
"Filename": "sample.cwa",
"Filesize(MB)": 65.1,
"Device": "Axivity",
"DeviceID": 2278,
"ReadErrors": 0,
"SampleRate": 100.0,
"ReadOK": 1,
"StartTime": "2013-10-21 10:00:07",
"EndTime": "2013-10-28 10:00:01",
"TotalWalking(min)": 655.75,
"TotalSteps": 43132,
...
}
Daily step count
----------------
steps
time
2013-10-21 5368.0
2013-10-22 7634.0
2013-10-23 10009.0
...
Output: outputs/sample/
Output files
By default, output files will be stored in a folder outputs/{filename}/
created in the current working directory. You can change the output path with the -o
flag:
$ stepcount sample.cwa -o /path/to/some/folder/
Processing CSV files
If a CSV file is provided, it must have the following header: time
, x
, y
, z
. For example:
time,x,y,z
2013-10-21 10:00:08.000,-0.078923,0.396706,0.917759
2013-10-21 10:00:08.010,-0.094370,0.381479,0.933580
2013-10-21 10:00:08.020,-0.094370,0.366252,0.901938
2013-10-21 10:00:08.030,-0.078923,0.411933,0.901938
...
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