braindecode.datasets.TUH#

class braindecode.datasets.TUH(path: str, recording_ids: list[int] | None = None, target_name: str | tuple[str, ...] | None = None, preload: bool = False, add_physician_reports: bool = False, rename_channels: bool = False, set_montage: bool = False, n_jobs: int = 1)[source]#

Temple University Hospital (TUH) EEG Corpus (www.isip.piconepress.com/projects/tuh_eeg/html/downloads.shtml#c_tueg).

Parameters:
  • path (str) – Parent directory of the dataset.

  • recording_ids (list(int) | int) – A (list of) int of recording id(s) to be read (order matters and will overwrite default chronological order, e.g. if recording_ids=[1,0], then the first recording returned by this class will be chronologically later then the second recording. Provide recording_ids in ascending order to preserve chronological order.).

  • target_name (str) – Can be ‘gender’, or ‘age’.

  • preload (bool) – If True, preload the data of the Raw objects.

  • add_physician_reports (bool) – If True, the physician reports will be read from disk and added to the description.

  • rename_channels (bool) – If True, rename the EEG channels to the standard 10-05 system.

  • set_montage (bool) – If True, set the montage to the standard 10-05 system.

  • n_jobs (int) – Number of jobs to be used to read files in parallel.

Examples using braindecode.datasets.TUH#

Multiple discrete targets with the TUH EEG Corpus

Multiple discrete targets with the TUH EEG Corpus

Process a big data EEG resource (TUH EEG Corpus)

Process a big data EEG resource (TUH EEG Corpus)