This standalone repository acts as use-case documentation for physiological data processing steps. The proposed workflow integrates community-based Ptyhon librairies such as phys2bids and neurokit2.
The repo is separated in three main modules, and provides a setp-by-step tutorial for each of them:
utils\
list_sub.py
: list all the physiological files for a given subject (and a given session).get_info.py
: retrieve physiological files information.match_acq_bids.py
: match Acqknowledge files (.acq) with the fMRI Nifti files (.nii.gz).
preproc\
convert.py
: use phys2bids to segment the acqknowledge files in runs following the BIDS format.clean.py
: implement functions to filter the physiological signals, and to remove the artifacts induced by the MRI.process.py
: build a processing pipeline based onclean.py
functions.quality.py
: provide a summary of the quality of the processed signal.
visu\
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Thanks to the generous data donation from a subject of the Courtois-Neuromod project, research communities like PhysioPy will benefit from common data access to test and optimize their physio data preparation workflows, using BIDS format.