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--- |
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title: NeuroNap |
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emoji: 🧠💤 |
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colorFrom: blue |
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colorTo: purple |
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sdk: gradio |
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sdk_version: 5.49.1 |
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app_file: main.py |
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pinned: false |
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python_version: 3.12.2 |
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license: mit |
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thumbnail: >- |
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https://cdn-uploads.huggingface.co/production/uploads/651643e699e8060f1e8abafb/p-2ydiwoc01OvDnIz6qaO.png |
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short_description: EEG-based sleep analysis tool |
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--- |
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# 🧠 NeuroNap |
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**NeuroNap** is an EEG-based sleep analysis tool that processes EEG CSV files to analyze sleep stages, generate hypnograms, visualize frequency spectra, and provide LLM-driven insights using **Gemini**. |
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Built with **Python** and **Gradio**, it uses **YASA** for sleep stage classification and **HMM** for clustering and offers an interactive interface for researchers and clinicians studying sleep patterns. |
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--- |
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## 🚀 Features |
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- **EEG Processing:** |
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Processes raw EEG CSV files using **bandpass** and **notch filters** to remove noise and artifacts, ensuring clean, reliable signal data. |
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- **Sleep Stage Classification:** |
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Utilizes **YASA** (Yet Another Sleep Analysis) to automatically classify sleep stages — **W, N1, N2, N3, and REM** — and compute essential sleep metrics such as **Total Sleep Time (TST)**, **Sleep Efficiency (SE)**, and **Wake After Sleep Onset (WASO)**. |
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- **Clustering:** |
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Applies **Hidden Markov Models (HMM)** to cluster EEG-derived features, revealing latent patterns and transitions across sleep stages. |
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- **Visualizations:** |
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Generates detailed plots for **EEG signals**, **hypnograms**, **frequency spectra**, and **band-specific waveforms**, allowing for intuitive data interpretation. |
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- **Sleep Statistics:** |
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Displays comprehensive sleep metrics (e.g., **Total Sleep Time**, **Sleep Efficiency**) with expandable tables showing additional parameters like **Time in Bed (TIB)**, **Sleep Period Time (SPT)**, and **latencies**. |
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- **LLM Insights:** |
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Integrates **Gemini** via **LangChain** for natural language interaction, using a **FAISS vector store** for context-aware sleep data insights. |
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- **Exportable Outputs:** |
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Enables easy download of results in **CSV** format (clean EEG, extracted features, clusters) and **PDF** format (visual reports and plots). |
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--- |
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## ⚙️ Installation |
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```bash |
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# Clone the repository |
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git clone https://github.com/yourusername/NeuroNap.git |
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cd NeuroNap |
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# Create a virtual environment |
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python -m venv venv |
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# Activate the environment |
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source venv/bin/activate # On Windows: venv\Scripts\activate |
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# Install dependencies |
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pip install -r requirements.txt |
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``` |
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🔑 **API Setup** |
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Set your Gemini API key in a `.env` file: |
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```bash |
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echo "GEMINI_API_KEY=your_api_key" > .env |
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``` |
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🧩 **Knowledge Embeddings** |
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Before running the app, generate embeddings from your knowledge PDFs: |
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```bash |
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python rag.py |
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``` |
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Place relevant research papers or notes in the knowledge/ folder before running the above command. |
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🖥️ **Usage** |
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Launch the Gradio interface: |
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```bash |
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python main.py |
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``` |
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Then: |
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1. **Upload** an EEG CSV file (e.g., `EEGDATA.csv`). |
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2. **View** sleep stage visualizations, HMM clusters, and frequency spectra. |
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3. **Interact** with the **"Chat with NeuroNap"** feature to get context-aware insights. |
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4. **Download** processed data and reports in **CSV** or **PDF** format. |
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## 📦 Requirements |
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- **Python 3.9+** |
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- See `requirements.txt` for the full dependency list |
