DS006940#

Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals

Access recordings and metadata through EEGDash.

Citation: Shantanu Sarkar, Kevin Nathan, Jose L. Contreras-Vidal (2025). Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals. 10.18112/openneuro.ds006940.v1.0.0

Modality: eeg Subjects: 7 Recordings: 14094 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006940

dataset = DS006940(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 = DS006940(cache_dir="./data", subject="01")

Advanced query

dataset = DS006940(
    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{ds006940,
  title = {Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals},
  author = {Shantanu Sarkar and Kevin Nathan and Jose L. Contreras-Vidal},
  doi = {10.18112/openneuro.ds006940.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds006940.v1.0.0},
}

About This Dataset#

EEG-Controlled Exoskeleton for Walking and Standing A Longitudinal Motor Imagery Study in Healthy Adults

Dataset Overview This dataset contains multimodal recordings from a brain–machine interface (BMI) training study involving seven healthy adult participants (ages 20–30, Mean = 24.3, SD = 3.8). The study focused on open-loop and closed-loop control of a lower-limb exoskeleton (Rex Bionics) using EEG and inertial sensor data. Each participant completed nine sessions over several weeks, structured into training and trial phases.

Experimental Design * Participants: 7 healthy adults (4 male, 3 female) * Sessions: 9 per participant * Training Phase: Motor imagery calibration

Dataset Information#

Dataset ID	`DS006940`
Title	Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals
Year	2025
Authors	Shantanu Sarkar, Kevin Nathan, Jose L. Contreras-Vidal
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006940.v1.0.0
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: 7
Recordings: 14094
Tasks: 135

Channels & sampling rate

Channels: 60
Sampling rate (Hz): 100.0
Duration (hours): 0.0

API Reference#

Use the DS006940 class to access this dataset programmatically.

class eegdash.dataset.DS006940(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006940. Modality: eeg; Experiment type: Motor; Subject type: Healthy. Subjects: 7; recordings: 935; tasks: 15.

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/ds006940 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006940

Examples

>>> from eegdash.dataset import DS006940
>>> dataset = DS006940(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