The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
dataset_id: string
version: string
file_count: int64
size_bytes: int64
manifest_url: string
repo_id: string
excluded_repository_control_files: list<item: null>
child 0, item: null
source_readme: string
raw_data_mirrored: bool
GeneratedBy: list<item: struct<Name: string, Description: string, Version: string>>
child 0, item: struct<Name: string, Description: string, Version: string>
child 0, Name: string
child 1, Description: string
child 2, Version: string
DatasetDOI: string
Funding: list<item: string>
child 0, item: string
Authors: list<item: string>
child 0, item: string
License: string
BIDSVersion: string
DatasetType: string
EthicsApprovals: list<item: string>
child 0, item: string
Version: string
Name: string
to
{'Name': Value('string'), 'BIDSVersion': Value('string'), 'DatasetType': Value('string'), 'License': Value('string'), 'Authors': List(Value('string')), 'Funding': List(Value('string')), 'EthicsApprovals': List(Value('string')), 'GeneratedBy': List({'Name': Value('string'), 'Description': Value('string'), 'Version': Value('string')}), 'DatasetDOI': Value('string'), 'Version': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
dataset_id: string
version: string
file_count: int64
size_bytes: int64
manifest_url: string
repo_id: string
excluded_repository_control_files: list<item: null>
child 0, item: null
source_readme: string
raw_data_mirrored: bool
GeneratedBy: list<item: struct<Name: string, Description: string, Version: string>>
child 0, item: struct<Name: string, Description: string, Version: string>
child 0, Name: string
child 1, Description: string
child 2, Version: string
DatasetDOI: string
Funding: list<item: string>
child 0, item: string
Authors: list<item: string>
child 0, item: string
License: string
BIDSVersion: string
DatasetType: string
EthicsApprovals: list<item: string>
child 0, item: string
Version: string
Name: string
to
{'Name': Value('string'), 'BIDSVersion': Value('string'), 'DatasetType': Value('string'), 'License': Value('string'), 'Authors': List(Value('string')), 'Funding': List(Value('string')), 'EthicsApprovals': List(Value('string')), 'GeneratedBy': List({'Name': Value('string'), 'Description': Value('string'), 'Version': Value('string')}), 'DatasetDOI': Value('string'), 'Version': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PROTEUS BCI Bordeaux — EEG/EMG Foundation Challenge 2026, Track 02
This repository hosts the complete scientific files of NEMAR nm000290,
snapshot v1.0.0. It includes every subject and recording, the
BIDS sidecars, and the source's sourcedata/ and code/ files where present.
All source files were verified against NEMAR's manifest checksums before upload.
Only DataLad control files and source .gitattributes files are omitted because
Hugging Face manages repository storage. The original README is preserved as
SOURCE_README.md.
EEG dataset from the PROTEUS brain-computer interface (BCI) project in Bordeaux, released for the EEG/EMG Foundation Challenge 2026 (Track 02). It contains recordings from 10 participants across 14 sessions (112 runs) performing three cued mental tasks: kinesthetic motor imagery, mental subtraction and word generation. Runs include resting baselines, calibration runs with sham feedback and online runs with real feedback, using Graz and BrainHero interfaces.
Load with the BIDS builder
These examples require datasets PR #9011 until its BIDS builder is released:
pip install "datasets[bids] @ git+https://github.com/bruAristimunha/datasets@feat/bids-biosignal"
from datasets import load_dataset
dataset = load_dataset("EEGDash/nm000290", split="train")
row = dataset[0]
recording = row["biosignal"]
print(recording)
samples = recording.get_data(start=0, stop=100)
print(row["metadata"])
There are 10 subjects and 112 recordings in the complete mirror. The example may select one subject; all subjects are stored here. Accessing a recording caches its subject/session/datatype folder and the repository’s JSON/TSV metadata. Other runs in that folder may also be downloaded. MNE then opens the cached recording lazily.
Source and attribution
- Source: https://nemar.org/dataset/nm000290
- Snapshot manifest: https://data.nemar.org/nm000290/v1.0.0/manifest.json
- Original authors, license and citations: source README and source metadata.
- Machine-readable checksums: nemar_manifest.json.
- Mirror version and omitted control files: mirror.json.
Selected using NEMAR's 30-day ranking of viewer data-chunk bytes. This ranking does not measure completed archive downloads.
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