EEGDash/ds005448

---
pretty_name: "STReEF"
license: cc0-1.0
tags:
- ieeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- other
- clinical-intervention
- epilepsy
size_categories:
- n<1K
task_categories:
- other
---

# STReEF

**Dataset ID:** `ds005448`

_Jelsma2024_

**Canonical aliases:** `STReEF`

> **At a glance:** IEEG · Other clinical/intervention · epilepsy · 13 subjects · 18 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="ds005448", 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 STReEF
ds = STReEF(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/ds005448")
```

## Dataset metadata

| | |
|---|---|
| **Subjects** | 13 |
| **Recordings** | 18 |
| **Tasks (count)** | 1 |
| **Channels** | 133 (×14), 109 (×2), 95 (×1), 161 (×1) |
| **Sampling rate (Hz)** | 2048 (×18) |
| **Total duration (h)** | 12.4 |
| **Size on disk** | 44.7 GB |
| **Recording type** | IEEG |
| **Experimental modality** | Other |
| **Paradigm type** | Clinical/Intervention |
| **Population** | Epilepsy |
| **Source** | openneuro |
| **License** | CC0 |

## Links

- **DOI:** [10.18112/openneuro.ds005448.v1.0.0](https://doi.org/10.18112/openneuro.ds005448.v1.0.0)
- **OpenNeuro:** [ds005448](https://openneuro.org/datasets/ds005448)
- **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/ds005448). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._

数据集展示名："STReEF"
授权协议：CC0 1.0
标签：
- 颅内脑电图（intracranial EEG, iEEG）
- 神经科学
- EEGDash
- 脑机接口
- PyTorch
- 其他
- 临床干预
- 癫痫
样本量类别：
- 样本量小于1000
任务类别：
- 其他

# STReEF

**数据集ID**：`ds005448`

_Jelsma等人2024年研究_

**规范别名**：`STReEF`

> **概览**：颅内脑电图（intracranial EEG, iEEG）· 其他临床/干预研究 · 癫痫 · 13名受试者 · 18条记录 · CC0授权

## 加载该数据集

本仓库为**指针仓库**，原始脑电图（electroencephalography, EEG）数据存储于其规范来源（OpenNeuro / NEMAR）；[EEGDash](https://github.com/eegdash/EEGDash) 可按需流式加载并返回PyTorch / braindecode数据集。

python
# 安装eegdash库
pip install eegdash
from eegdash import EEGDashDataset

ds = EEGDashDataset(dataset="ds005448", cache_dir="./cache")
print(len(ds), "条记录")

你也可以通过规范别名加载该数据集——这些别名已在`eegdash.dataset`中注册为类：
python
from eegdash.dataset import STReEF
ds = STReEF(cache_dir="./cache")

若该数据集已按照braindecode的Zarr布局镜像至Hugging Face Hub，你也可以直接拉取：
python
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/ds005448")

## 数据集元数据

| 字段 | 内容 |
|---|---|
| **受试者数量** | 13 |
| **记录条数** | 18 |
| **任务（数量）** | 1 |
| **导联数** | 133（×14）、109（×2）、95（×1）、161（×1） |
| **采样率（Hz）** | 2048（×18） |
| **总时长（小时）** | 12.4 |
| **磁盘占用大小** | 44.7 GB |
| **记录类型** | 颅内脑电图（intracranial EEG, iEEG） |
| **实验模态** | 其他 |
| **范式类型** | 临床/干预 |
| **研究人群** | 癫痫患者 |
| **数据来源** | OpenNeuro |
| **授权协议** | CC0 |

## 相关链接

- **DOI**：[10.18112/openneuro.ds005448.v1.0.0](https://doi.org/10.18112/openneuro.ds005448.v1.0.0)
- **OpenNeuro平台**：[ds005448](https://openneuro.org/datasets/ds005448)
- **浏览700+数据集**：[EEGDash 数据集目录](https://huggingface.co/spaces/EEGDash/catalog)
- **文档**：<https://eegdash.org>
- **代码仓库**：<https://github.com/eegdash/EEGDash>

---

_本内容自动从[dataset_summary.csv](https://github.com/eegdash/EEGDash/blob/main/eegdash/dataset/dataset_summary.csv)及[EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds005448)生成。请勿手动编辑此文件——请更新上游源并重新运行`scripts/push_metadata_stubs.py`脚本。_