Datasets:

EEGDash
/

ds004541

pretty_name: Multimodal EEG-fNIRS data from patients undergoing general anesthesia
license: cc0-1.0
tags:
  - eeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - anesthesia
  - clinical-intervention
  - surgery
size_categories:
  - n<1K
task_categories:
  - other

Multimodal EEG-fNIRS data from patients undergoing general anesthesia

Dataset ID: ds004541

Ferron2023

Canonical aliases: Ferron2019

At a glance: EEG, FNIRS · Anesthesia clinical/intervention · surgery · 8 subjects · 18 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="ds004541", 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 Ferron2019
ds = Ferron2019(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/ds004541")

Dataset metadata


Subjects	8
Recordings	18
Tasks (count)	1
Channels	59 (×9), 40 (×5), 30 (×3), 38 (×1)
Sampling rate (Hz)	1000 (×9), 7.8125 (×9)
Total duration (h)	12.1
Size on disk	2.9 GB
Recording type	EEG, FNIRS
Experimental modality	Anesthesia
Paradigm type	Clinical/Intervention
Population	Surgery
Source	openneuro
License	CC0

Multimodal EEG-fNIRS data from patients undergoing general anesthesia

Load this dataset

Dataset metadata

Links