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| title: Sleep Stage Classifier | |
| emoji: 😴 | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: 6.12.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Classify sleep stages from raw EEG signals | |
| python_version: '3.11' | |
| # 😴 Sleep Stage Classification | |
| Upload a CSV, TXT, or NPY file containing raw EEG signal data (100 Hz sampling rate). | |
| The model classifies the signal into 30-second epochs across 6 sleep stages: **Wake, N1, N2, N3, N4, REM**. | |
| ## Model Architecture | |
| - **Type**: 1D Convolutional Neural Network | |
| - **Framework**: PyTorch | |
| - **Input**: Single-channel EEG, 3000 samples per epoch (30s at 100 Hz) | |
| - **Output**: 6-class classification logits → softmax probabilities | |
| ## API Usage | |
| ```python | |
| from gradio_client import Client | |
| client = Client("<your-username>/sleep-stage-classifier") | |
| result = client.predict(file="path/to/eeg.csv") | |
| print(result) | |
| ``` | |
| ## Lovable / Frontend Integration | |
| ```javascript | |
| import { Client } from "@gradio/client"; | |
| const client = await Client.connect( | |
| "https://<your-username>-sleep-stage-classifier.hf.space" | |
| ); | |
| const result = await client.predict("/predict", { file: yourFile }); | |
| console.log(result.data); | |
| ``` |