mne.datasets.sleep_physionet.age.fetch_data

mne.datasets.sleep_physionet.age.fetch_data(subjects, recording=[1, 2], path=None, force_update=False, update_path=None, base_url='https://physionet.org/physiobank/database/sleep-edfx/sleep-cassette/', verbose=None)[source]

Get paths to local copies of PhysioNet Polysomnography dataset files.

This will fetch data from the publicly available subjects from PhysioNet’s study of age effects on sleep in healthy subjects [R008cc7a4bd91-1]_[R008cc7a4bd91-2]_. This corresponds to a subset of 20 subjects, 10 males and 10 females that were 25-34 years old at the time of the recordings. There are two night recordings per subject except for subject 13 since the second record was lost.

See more details in physionet website.

Parameters
subjectslist of int

The subjects to use. Can be in the range of 0-19 (inclusive).

recordinglist of int

The night recording indices. Valid values are : [1], [2], or [1, 2].

pathNone | str

Location of where to look for the PhysioNet data storing location. If None, the environment variable or config parameter MNE_DATASETS_PHYSIONET_SLEEP_PATH is used. If it doesn’t exist, the “~/mne_data” directory is used. If the Polysomnography dataset is not found under the given path, the data will be automatically downloaded to the specified folder.

force_updatebool

Force update of the dataset even if a local copy exists.

update_pathbool | None

If True, set the MNE_DATASETS_EEGBCI_PATH in mne-python config to the given path. If None, the user is prompted.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns
pathslist

List of local data paths of the given type.

Notes

For example, one could do:

>>> from mne.datasets import sleep_physionet
>>> sleep_physionet.age.fetch_data(subjects=[0])  

This would download data for subject 0 if it isn’t there already.

References

1

MS Mourtazaev, B Kemp, AH Zwinderman, HAC Kamphuisen. Age and gender affect different characteristics of slow waves in the sleep EEG. Sleep 18(7):557–564 (1995).

2

Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. (2000) PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220

Examples using mne.datasets.sleep_physionet.age.fetch_data