BaselineCorrection

class torcheeg.transforms.BaselineCorrection(axis=-1)

A transform method to subtract the mean of baseline signal from EEG.

TorchEEG recommends using this class in online_transform for higher processing speed. Even though, this class is also supported in offline_transform. Usually, the baseline needs the same transformation as the experimental signal, please add apply_to_baseline=True to all transforms before this operation to ensure that the transformation is performed on the baseline signal

from torcheeg import transforms

t = transforms.BaseCorrection()

t(eeg=np.random.randn(32, 128), baseline=np.random.randn(32, 128))['eeg'].shape
>>> (32,128)

__call__(*args, eeg: any, baseline=None, **kwargs)

Call self as a function.