DS005262#

ArEEG: Arabic Inner Speech EEG dataset

Access recordings and metadata through EEGDash.

Citation: Donia Metwalli, Eslam Ahmed, Antony Emil, Yousef A. Radwan, Mariam Barakat, Anas Ahmed, Amro Omar, Sahar Selim (2024). ArEEG: Arabic Inner Speech EEG dataset. 10.18112/openneuro.ds005262.v1.0.1

Modality: eeg Subjects: 12 Recordings: 561 License: CC0 Source: openneuro Citations: 0.0

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS005262

dataset = DS005262(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Query & Filter

Filter by subject

dataset = DS005262(cache_dir="./data", subject="01")

Advanced query

dataset = DS005262(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Iterate recordings

for rec in dataset:
    print(rec.subject, rec.raw.info['sfreq'])

Cite This Dataset

If you use this dataset in your research, please cite the original authors.

BibTeX

@dataset{ds005262,
  title = {ArEEG: Arabic Inner Speech EEG dataset},
  author = {Donia Metwalli and Eslam Ahmed and Antony Emil and Yousef A. Radwan and Mariam Barakat and Anas Ahmed and Amro Omar and Sahar Selim},
  doi = {10.18112/openneuro.ds005262.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds005262.v1.0.1},
}

About This Dataset#

ArEEG: Arabic EEG Dataset

This dataset is a collection of Inner Speech EEG recordings from 12 subjects, 7 males and 5 females with visual cues written in Modern Standard Arabic. Go to GitHub Repository_ for usage instructions.

Dataset Information#

Dataset ID	`DS005262`
Title	ArEEG: Arabic Inner Speech EEG dataset
Year	2024
Authors	Donia Metwalli, Eslam Ahmed, Antony Emil, Yousef A. Radwan, Mariam Barakat, Anas Ahmed, Amro Omar, Sahar Selim
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds005262.v1.0.1
Source links	OpenNeuro \| NeMAR \| Source URL

Found an issue with this dataset?

If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!

Report an Issue on GitHub

Technical Details#

Subjects & recordings

Subjects: 12
Recordings: 561
Tasks: —

Channels & sampling rate

Channels: 8
Sampling rate (Hz): 250.0
Duration (hours): 0.0

API Reference#

Use the DS005262 class to access this dataset programmatically.

class eegdash.dataset.DS005262(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds005262. Modality: eeg; Experiment type: other; Subject type: Healthy. Subjects: 12; recordings: 186; tasks: 1.

Parameters:

cache_dir (str | Path) – Directory where data are cached locally.
query (dict | None) – Additional MongoDB-style filters to AND with the dataset selection. Must not contain the key dataset.
s3_bucket (str | None) – Base S3 bucket used to locate the data.
**kwargs (dict) – Additional keyword arguments forwarded to EEGDashDataset.

data_dir#

Local dataset cache directory (cache_dir / dataset_id).

Type:: Path

query#

Merged query with the dataset filter applied.

Type:: dict

records#

Metadata records used to build the dataset, if pre-fetched.

Type:: list[dict] | None

Notes

Each item is a recording; recording-level metadata are available via dataset.description. query supports MongoDB-style filters on fields in ALLOWED_QUERY_FIELDS and is combined with the dataset filter. Dataset-specific caveats are not provided in the summary metadata.

References

OpenNeuro dataset: https://openneuro.org/datasets/ds005262 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds005262

Examples

>>> from eegdash.dataset import DS005262
>>> dataset = DS005262(cache_dir="./data")
>>> recording = dataset[0]
>>> raw = recording.load()

__init__(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

save(path, overwrite=False)[source]#

Save the dataset to disk.

Parameters:

path (str or Path) – Destination file path.
overwrite (bool, default False) – If True, overwrite existing file.

Return type:

None