| title: Health Monitoring System | |
| emoji: 🏥 | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: docker | |
| pinned: false | |
| # Health Monitoring System | |
| A comprehensive health monitoring system that provides: | |
| - Heart rate analysis | |
| - ECG anomaly detection | |
| - Audio analysis | |
| - Real-time emergency handling | |
| - User authentication and management | |
| ## Features | |
| - Real-time health monitoring | |
| - Machine learning-based anomaly detection | |
| - Interactive visualizations | |
| - Emergency response system | |
| - User-friendly interface | |
| ## Technical Details | |
| - Built with Flask and SocketIO | |
| - Uses TensorFlow and PyTorch for ML models | |
| - Firebase integration for real-time data | |
| - WebSocket support for live updates | |
| ## Setup Instructions | |
| 1. Clone this repository | |
| 2. Install dependencies: `pip install -r requirements.txt` | |
| 3. Run the application: `python app.py` | |
| ## API Endpoints | |
| - `/`: Main dashboard | |
| - `/predict`: Health prediction endpoint | |
| - `/emergency`: Emergency response endpoint | |
| ## Model Information | |
| - Heart Rate Model: Trained on MIT-BIH Arrhythmia Database | |
| - ECG Anomaly Detection: Autoencoder-based model | |
| - Audio Analysis: Custom CNN architecture | |
| ## License | |
| MIT License |