---
pretty_name: "MUniverse Avrillon et al 2024"
license: cc0-1.0
tags:
  - eeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
size_categories:
  - n<1K
task_categories:
  - other
---

# MUniverse Avrillon et al 2024

**Dataset ID:** `nm000159`

_Avrillon2024_

> **At a glance:** EMG · 16 subjects · 124 recordings · CC0 BY 4.0

## Load this dataset

This repo is a **pointer**. The raw EEG data lives at its canonical source
(OpenNeuro / NEMAR); [EEGDash](https://github.com/eegdash/EEGDash) streams it
on demand and returns a PyTorch / braindecode dataset.

```python
# pip install eegdash
from eegdash import EEGDashDataset

ds = EEGDashDataset(dataset="nm000159", cache_dir="./cache")
print(len(ds), "recordings")
```

If the dataset has been mirrored to the HF Hub in braindecode's Zarr layout,
you can also pull it directly:

```python
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/nm000159")
```


## Dataset metadata

| | |
|---|---|
| **Subjects** | 16 |
| **Recordings** | 124 |
| **Tasks (count)** | 8 |
| **Channels** | 258 (×124) |
| **Sampling rate (Hz)** | 2048 (×124) |
| **Total duration (h)** | 1.6 |
| **Size on disk** | 5.5 GB |
| **Recording type** | EMG |
| **Source** | nemar |
| **License** | CC0 BY 4.0 |

## Links

- **DOI:** [https://doi.org/10.7910/DVN/L9OQY7](https://doi.org/https://doi.org/10.7910/DVN/L9OQY7)
- **NEMAR:** [nm000159](https://nemar.org/dataexplorer/detail?dataset_id=nm000159)
- **Browse 700+ datasets:** [EEGDash catalog](https://huggingface.co/spaces/EEGDash/catalog)
- **Docs:** <https://eegdash.org>
- **Code:** <https://github.com/eegdash/EEGDash>

---

_Auto-generated from [dataset_summary.csv](https://github.com/eegdash/EEGDash/blob/main/eegdash/dataset/dataset_summary.csv) and the [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/nm000159). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._