Parkinson`s Disease Kit
Project description
#PDKIT
Example how to use pdkit to calculate Tremor amplitude and frequency:
>>> import pdkit >>> tp = pdkit.TremorProcessor() >>> ts = pdkit.TremorTimeSeries().load(filename) >>> amplitude, frequency = tp.process(ts)where, filename is the data path to load, by default in the cloudUPDRS format.
PDKit can also read data in the MPower format, just like:
>>> ts = pdkit.TremorTimeSeries().load(filename, 'mpower')where, filename is the data path to load in mpower format.
To calculate Welch, as a robust alternative to using Fast Fourier Transform, use like:
>>> amplitude, frequency = tp.process(ts, 'welch')
Example how to use pdkit to calculate various Gait features:
>>> import pdkit >>> ts = pdkit.GaitTimeSeries().load(filename) >>> gp = pdkit.GaitProcessor() >>> freeze_times, freeze_indexes, locomotion_freezes = gp.freeze_of_gait(ts) >>> frequency_of_peaks = gp.frequency_of_peaks(ts) >>> speed_of_gait = gp.speed_of_gait(ts) >>> step_regularity, stride_regularity, walk_symmetry = gp.walk_regularity_symmetry(ts)where, filename is the data path to load, by default in the cloudUPDRS format.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pdkit-0.3.3.tar.gz
(17.7 kB
view hashes)
Built Distribution
pdkit-0.3.3-py2.py3-none-any.whl
(20.6 kB
view hashes)
Close
Hashes for pdkit-0.3.3-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 00bc05fb9f6063d696e594f7d40de38577773f9fe33e566c2c28326ae216c30f |
|
MD5 | e7dac0b9a83caa792f537d3cab37c18f |
|
BLAKE2b-256 | a240075dba63720a1bfb62562d21ddc90936b1199b30b62cca12db7126458345 |