Seizure Forecasting System

This project implements a seizure forecasting system using physiological data from wrist-worn devices. The system processes multivariate time-series data, extracts features, and uses an LSTM-based neural network for predictions.

Setup Instructions

1. Clone the repository and navigate to the project folder.

2. Install dependencies:

   pip install -r requirements.txt

3. Add your data files to the data/ directory.

   • wearable_data.csv: Sensor data from wrist-worn devices.
   • seizure_events.csv: Seizure labels.

4. Run the pipeline:

   python main.py

Project Structure

seizure_forecasting/
│
├── data/
│   ├── wearable_data.csv          # Placeholder for raw wearable device data
│   ├── seizure_events.csv         # Placeholder for seizure event labels
│
├── src/
│   ├── data_processing.py         # Functions for processing data
│   ├── model.py                   # LSTM model definition
│   ├── training.py                # Training and evaluation pipeline
│   ├── evaluation.py              # Evaluation metrics
│
├── main.py                        # Script to run the entire pipeline
│
└── requirements.txt               # List of required Python packages

Future Enhancements

• Advanced feature engineering.
• Patient-specific models.
• Real-time processing optimization.