eegdash.hbn.preprocessing module#

Preprocessing utilities specific to the Healthy Brain Network dataset.

This module contains preprocessing classes and functions designed specifically for HBN EEG data, including specialized annotation handling for eyes-open/eyes-closed paradigms and other HBN-specific preprocessing steps.

class eegdash.hbn.preprocessing.hbn_ec_ec_reannotation[source]

Bases: Preprocessor

Preprocessor to reannotate HBN data for eyes-open/eyes-closed events.

This preprocessor is specifically designed for Healthy Brain Network (HBN) datasets. It identifies existing annotations for “instructed_toCloseEyes” and “instructed_toOpenEyes” and creates new, regularly spaced annotations for “eyes_closed” and “eyes_open” segments, respectively.

This is useful for creating windowed datasets based on these new, more precise event markers.

Notes

This class inherits from braindecode.preprocessing.Preprocessor and is intended to be used within a braindecode preprocessing pipeline.

transform(raw: Raw) → Raw[source]

Create new annotations for eyes-open and eyes-closed periods.

This function finds the original “instructed_to…” annotations and generates new annotations every 2 seconds within specific time ranges relative to the original markers: - “eyes_closed”: 15s to 29s after “instructed_toCloseEyes” - “eyes_open”: 5s to 19s after “instructed_toOpenEyes”

The original annotations in the mne.io.Raw object are replaced by this new set of annotations.

Parameters:

raw (mne.io.Raw) – The raw MNE object containing the HBN data and original annotations.

Returns:

The raw MNE object with the modified annotations.

Return type:

mne.io.Raw