🧠 NeuroTwin: Brain Digital Twin Platform

🔮 Advanced EEG Analysis & Neural Simulation Platform 🧬

🚀 What is NeuroTwin?

NeuroTwin is a cutting-edge platform that creates personalized Digital Brain Twins from EEG data, enabling medical professionals to:

• 📊 Analyze EEG patterns for neurological conditions
• 💊 Simulate medication responses before prescription
• 🔮 Predict surgical outcomes with high accuracy
• 🧠 Visualize brain activity patterns in 3D
• 🤖 Leverage AI for automated clinical insights

Note: NeuroTwin is a next-generation neural modeling platform that transforms how clinicians interact with patient brain data.

✨ Key Features

🔍 EEG Analysis	🧪 Treatment Simulation	🧠 Brain Visualization	🤖 AI Assistant
Epilepsy detection	Medication response	3D neural mapping	Clinical insights
Seizure risk	Surgical outcomes	Temporal activity tracking	Report generation
Cognitive patterns	Side effect prediction	Regional abnormality view	Diagnostic support

🛠️ Technology Stack

Frontend

• Next.js 15 - React framework with SSR & App Router
• React 19 - Component-based UI library
• Tailwind CSS - Utility-first styling
• Shadcn UI - Accessible component library
• Electron - Desktop application support (optional)

Backend

• FastAPI - High-performance Python API framework
• Supabase - Database & authentication
• PyTorch - Neural network models
• MNE - EEG/MEG data processing
• Groq API - LLM integration for clinical insights

🚀 Getting Started

Prerequisites

• Node.js 18+
• Python 3.8+
• Supabase account
• Groq API key

1️⃣ Clone the Repository

git clone https://github.com/yourusername/NeuroTwin.git
cd NeuroTwin

2️⃣ Backend Setup

NeuroTwin has two backend services: a FastAPI server and a Flask server. Both need to be running for full functionality.

FastAPI Backend

# Create and activate virtual environment
cd server
python -m venv venv

# Linux/macOS
source venv/bin/activate

# Windows
venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Create .env file (see template below)
# Start the FastAPI server
uvicorn main:app --reload --host 0.0.0.0 --port 8000

Flask Backend

# With the same virtual environment active
cd server

# Start the Flask server
python app.py
# This will run on port 5000 by default

Backend .env Template:

SUPABASE_URL=your-supabase-url
SUPABASE_KEY=your-supabase-anon-key
SUPABASE_SERVICE_KEY=your-supabase-service-role-key
GROQ_API_KEY=your-groq-api-key
SECRET_KEY=your-jwt-secret-key
ALGORITHM=HS256

3️⃣ Frontend Setup

# Navigate to client directory
cd client

# Install dependencies
npm install

# Start development server
npm run dev

Client .env.local Template:

NEXT_PUBLIC_API_URL=http://localhost:8000

4️⃣ Access the Application

• Web App: http://localhost:3000
• API Documentation: http://localhost:8000/docs

🧪 Key Modules

🔍 EEG Analysis

Upload and process EEG data to create personalized brain models and detect neurological conditions.

🧠 Brain Viewer

Interactive 3D visualization of brain activity patterns, allowing temporal exploration and abnormality detection.

💊 Medication Simulation

Simulate the effects of medications on brain activity with personalized Digital Twin models.

🔪 Surgical Simulation

Predict outcomes of different surgical approaches for neurological conditions.

📊 Patient Records

Manage patient data, EEG recordings, and analysis results in a secure dashboard.

💻 Development Commands

Backend

# Run tests
pytest

# Generate OpenAPI schema
python -c "import main; print(main.app.openapi())" > openapi.json

# Create migration
python -m alembic revision --autogenerate -m "migration message"

# Apply migration
python -m alembic upgrade head

Frontend

# Run development server
npm run dev

# Build for production
npm run build

# Start production server
npm start

# Run Electron app (desktop)
npm run electron-dev

# Build Electron app
npm run electron-build

🌍 Deployment

Backend Deployment

# Using Gunicorn
gunicorn -w 4 -k uvicorn.workers.UvicornWorker main:app

Frontend Deployment

# Build Next.js app
npm run build

# Deploy to Vercel
vercel

📱 Desktop Application

NeuroTwin can also run as a desktop application using Electron:

# Run Electron dev mode
npm run electron-dev

# Package for distribution
npm run electron-build

🔒 Security Notes

• All EEG data is processed locally before storage
• End-to-end encryption for patient records
• Role-based access control for clinical teams
• Compliance with healthcare data regulations

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin amazing-feature)
5. Open a Pull Request

👥 Team

• Harshal - Developer - GitHub
• Ghruank - Developer - GitHub
• Prathamesh - Developer - GitHub
• Yadnesh - Developer - GitHub

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NeuroTwin: Transforming Neurological Care with Digital Brain Twins

Made with ❤️ by the NeuroTwin Team