diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e0828f2f6238e8bb396ea5af2a28be78c933b57a --- /dev/null +++ b/README.md @@ -0,0 +1,102 @@ +--- +tags: +- braindecode +- eeg +- neuroscience +- brain-computer-interface +- deep-learning +license: unknown +--- + +# EEG Dataset + +This dataset was created using [braindecode](https://braindecode.org), a deep +learning library for EEG/MEG/ECoG signals. + +## Dataset Information + +| Property | Value | +|----------|------:| +| Recordings | 1 | +| Type | Windowed (from Epochs object) | +| Channels | 26 | +| Sampling frequency | 250 Hz | +| Total duration | 0:03:11 | +| Windows/samples | 48 | +| Size | 0.03 MB | +| Format | zarr | + +## Quick Start + +```python +from braindecode.datasets import BaseConcatDataset + +# Load from Hugging Face Hub +dataset = BaseConcatDataset.pull_from_hub("username/dataset-name") + +# Access a sample +X, y, metainfo = dataset[0] +# X: EEG data [n_channels, n_times] +# y: target label +# metainfo: window indices +``` + +## Training with PyTorch + +```python +from torch.utils.data import DataLoader + +loader = DataLoader(dataset, batch_size=32, shuffle=True, num_workers=4) + +for X, y, metainfo in loader: + # X: [batch_size, n_channels, n_times] + # y: [batch_size] + pass # Your training code +``` + +## BIDS-inspired Structure + +This dataset uses a **BIDS-inspired** organization. Metadata files follow BIDS +conventions, while data is stored in Zarr format for efficient deep learning. + +**BIDS-style metadata:** +- `dataset_description.json` - Dataset information +- `participants.tsv` - Subject metadata +- `*_events.tsv` - Trial/window events +- `*_channels.tsv` - Channel information +- `*_eeg.json` - Recording parameters + +**Data storage:** +- `dataset.zarr/` - Zarr format (optimized for random access) + +``` +sourcedata/braindecode/ +├── dataset_description.json +├── participants.tsv +├── dataset.zarr/ +└── sub-