| --- |
| pretty_name: "HUP iEEG Epilepsy Dataset" |
| license: cc0-1.0 |
| tags: |
| - ieeg |
| - neuroscience |
| - eegdash |
| - brain-computer-interface |
| - pytorch |
| - other |
| - clinical-intervention |
| - epilepsy |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| --- |
| |
| # HUP iEEG Epilepsy Dataset |
|
|
| **Dataset ID:** `ds004100` |
|
|
| _Bernabei2022_ |
|
|
| **Canonical aliases:** `HUPiEEG` |
|
|
| > **At a glance:** IEEG · Other clinical/intervention · epilepsy · 57 subjects · 319 recordings · CC0 |
|
|
| ## 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="ds004100", cache_dir="./cache") |
| print(len(ds), "recordings") |
| ``` |
|
|
| You can also load it by canonical alias — these are registered classes in `eegdash.dataset`: |
|
|
| ```python |
| from eegdash.dataset import HUPiEEG |
| ds = HUPiEEG(cache_dir="./cache") |
| ``` |
|
|
| 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/ds004100") |
| ``` |
|
|
|
|
| ## Dataset metadata |
|
|
| | | | |
| |---|---| |
| | **Subjects** | 57 | |
| | **Recordings** | 319 | |
| | **Tasks (count)** | 2 | |
| | **Channels** | 122 (×21), 128 (×18), 118 (×17), 172 (×15), 126 (×14), 104 (×13), 82 (×12), 127 (×12), 180 (×12), 96 (×12), 92 (×7), 80 (×7), 190 (×7), 108 (×7), 74 (×7), 121 (×7), 136 (×7), 109 (×7), 117 (×7), 102 (×7), 174 (×7), 149 (×7), 120 (×7), 163 (×6), 98 (×6), 63 (×5), 186 (×5), 162 (×5), 100 (×5), 164 (×5), 88 (×5), 59 (×5), 116 (×5), 52 (×5), 71 (×5), 105 (×4), 90 (×4), 61 (×4), 85 (×3), 94 (×2), 192 (×2), 232 (×1) | |
| | **Sampling rate (Hz)** | 512 (×165), 1024 (×78), 500 (×69), 256 (×7) | |
| | **Total duration (h)** | 25.7 | |
| | **Size on disk** | 13.2 GB | |
| | **Recording type** | IEEG | |
| | **Experimental modality** | Other | |
| | **Paradigm type** | Clinical/Intervention | |
| | **Population** | Epilepsy | |
| | **Source** | openneuro | |
| | **License** | CC0 | |
| | **NEMAR citations** | 21.0 | |
|
|
| ## Links |
|
|
| - **DOI:** [10.18112/openneuro.ds004100.v1.1.3](https://doi.org/10.18112/openneuro.ds004100.v1.1.3) |
| - **OpenNeuro:** [ds004100](https://openneuro.org/datasets/ds004100) |
| - **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/ds004100). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._ |
|
|
