metadata
pretty_name: Ear-EEG Sleep Monitoring 2019 (EESM19)
license: cc0-1.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- sleep
size_categories:
- n<1K
task_categories:
- other
Ear-EEG Sleep Monitoring 2019 (EESM19)
Dataset ID: ds005185
Mikkelsen2024_Ear_Sleep_Monitoring
Canonical aliases: EESM19
At a glance: EEG · Sleep sleep · healthy · 20 subjects · 356 recordings · CC0
Load this dataset
This repo is a pointer. The raw EEG data lives at its canonical source (OpenNeuro / NEMAR); EEGDash streams it on demand and returns a PyTorch / braindecode dataset.
# pip install eegdash
from eegdash import EEGDashDataset
ds = EEGDashDataset(dataset="ds005185", cache_dir="./cache")
print(len(ds), "recordings")
You can also load it by canonical alias — these are registered classes in eegdash.dataset:
from eegdash.dataset import EESM19
ds = EESM19(cache_dir="./cache")
If the dataset has been mirrored to the HF Hub in braindecode's Zarr layout, you can also pull it directly:
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/ds005185")
Dataset metadata
| Subjects | 20 |
| Recordings | 356 |
| Tasks (count) | 3 |
| Channels | 25 (×156) |
| Sampling rate (Hz) | 500 (×156) |
| Total duration (h) | 1,365.6 |
| Size on disk | 267.6 GB |
| Recording type | EEG |
| Experimental modality | Sleep |
| Paradigm type | Sleep |
| Population | Healthy |
| Source | openneuro |
| License | CC0 |
Links
- DOI: 10.18112/openneuro.ds005185.v1.0.2
- OpenNeuro: ds005185
- Browse 700+ datasets: EEGDash catalog
- Docs: https://eegdash.org
- Code: https://github.com/eegdash/EEGDash
Auto-generated from dataset_summary.csv and the EEGDash API. Do not edit this file by hand — update the upstream source and re-run scripts/push_metadata_stubs.py.