A comprehensive digital health tracking application that creates your personalized digital twin to learn from your daily habits, predict health trends, and guide you toward a better lifestyle through AI-powered insights.

This project is an open-source prototype developed as part of a university AI course to demonstrate the integration of health tracking, data visualization, and AI-driven recommendations in a modern web application. It serves as both an educational tool and a functional demonstration of digital health concepts.

Monitor your daily movement, exercise patterns, and physical activities with smart habit tracking. Set goals, track workouts, and view detailed activity analytics.

Track your eating habits, log meals, and receive personalized nutrition recommendations based on your dietary patterns and health goals.

Understand your sleep patterns, track sleep quality, and get insights to improve your rest. Analyze sleep cycles and receive optimization suggestions.

Access mental wellness features, guided meditation sessions, breathing exercises, and stress management tools for holistic health.

Comprehensive dashboard displaying all your health metrics, trends, and vital statistics in one centralized location.

• Health Avatar: Interactive visual representation that reflects your current health status and progress
• Dashboard: Centralized hub with real-time health metrics, charts, and personalized insights
• Devices: Integration capabilities for connected health devices and wearables
• Social (Friends): Connect with friends, share progress, and motivate each other
• Leaderboard: Participate in health challenges and friendly competitions
• Profile: Manage account settings, notifications, preferences, and premium features

Each health domain includes an AI chat assistant that provides:

• Personalized advice and recommendations
• Answers to health-related questions
• Context-aware insights based on your data
• Motivational support and guidance

Secure OTP-based email verification ensures safe user registration and login. Features include:

• Email verification with one-time passwords
• Secure session management
• User data protection and privacy

Complete in-app documentation available for:

• All feature modules (Activity, Nutrition, Sleep, Mindfulness, Health, Avatar)
• Authentication and security implementation
• API integration guides
• User tutorials and best practices

• Framework: Next.js 16 with App Router
• Language: TypeScript for type safety
• Styling: Tailwind CSS with custom animations and responsive design
• State Management: React hooks with localStorage/sessionStorage
• Responsive: Fully Responsive Web-Application

1. Clone the repository

   git clone https://github.com/shakurt/digital-health-twin.git
   cd digital-health-twin

2. Install dependencies

   npm install

3. Run the development server

   npm run dev

4. Open your browser Navigate to http://localhost:3000

• 🌟 Open Source: Freely available on GitHub for learning and contribution
• 🎓 University AI Course: Created as an academic project to explore AI in healthcare
• 🔬 Prototype: Educational and demonstration-focused implementation
• ✨ Vibe Coding: Built with creativity, innovation, and modern development practices
• 📝 Well-Documented: Extensive documentation for all features and implementations

This project is open source and available under the MIT License.

Note: This is a prototype for educational and presentation purposes. Always consult healthcare professionals for medical advice.