Swap Health - AI-Powered Fitness & Healthcare App

A comprehensive React Native mobile application that combines AI-powered exercise tracking, medical consultations, and health monitoring capabilities. Built with pose estimation technology and integrated healthcare provider dashboards.

🎥 Watch Demo Video

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👥 Team Members

Yash Srivastava Roll No: 23BDS071	Karan Kabdal Roll No: 23BDS028
Yash Birje Roll No: 23BDS070

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📁 Folder Structure

.
├── .expo/
├── Components/
│
├── Admin/
│
├── Auth/
│   ├── AuthScreen.tsx
│   ├── LoginScreen.tsx
│   └── RegisterScreen.tsx
│
├── Chatbot/
│   ├── HealthChatbot.tsx
│   └── README.md
│
├── Common/
│
├── Consent/
│
├── Dashboard/
│   ├── DoctorDashboard.tsx
│   ├── HealthMetrics.tsx
│   ├── PatientAnalytics.tsx
│   ├── PatientDashboard.tsx
│   ├── PatientList.tsx
│   └── WorkoutSuggestions.tsx
│
├── DataSharing/
│
├── Exercise/
│
├── ExercisePrescription/
│   └── DoctorPrescriptionInterface.tsx
│
├── Profile/
│
├── Welcome.tsx
│
├── assets/
│
├── backend/
│   ├── __pycache__/
│   ├── IMPLEMENTATION_SUMMARY....
│   ├── README.md
│   ├── file_handler.py
│   ├── main.py
│   ├── requirements.txt
│   ├── swap_health.db
│   ├── tensorflow_config.py
│   └── test_endpoints.py
│
├── config/
│
├── docs/
│
├── exercises/
│
├── fitness/
│
├── node_modules/
│
├── scripts/
│
├── services/
│   ├── authService.ts
│   ├── cameraService.ts
│   ├── cameraServiceExample.ts
│   ├── consentService.ts
│   ├── databaseService.ts
│   ├── exerciseAnalysisService.ts
│   ├── exercisePrescriptionService.ts
│   ├── fitnessBackendService.ts
│   ├── fitnessBackendServiceExample.ts
│   ├── huggingFaceService.ts
│   ├── mockApiService.ts
│   ├── monitoringService.ts
│   ├── networkConfig.ts
│   ├── networkService.ts
│   ├── secureDataService.ts
│   ├── simpleFitnessService.ts
│   └── squatAnalysisService.ts
│
├── types/
│
├── .env
├── .gitattributes
├── App.tsx
├── README.md
├── app.json
├── babel.config.js
├── index.ts
├── package-lock.json
├── package.json
├── swap_health.db
└── tsconfig.json

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🌟 Features

🏃‍♂️ AI-Powered Exercise Tracking

• Real-time Pose Estimation: MediaPipe-powered exercise form analysis
• 25+ Exercise Types: From strength training to therapeutic exercises
• Live Form Feedback: Real-time corrections and rep counting
• Video Analysis: Upload workout videos for detailed analysis
• Progress Tracking: Monitor improvements over time

🤖 AI Health Assistant

• Medical Chatbot: Powered by Hugging Face's free medical AI models
• Contextual Responses: Tailored advice based on user medical profile
• Safety-First Design: Always recommends professional medical consultation
• Offline Fallback: Works without internet connection

👩‍⚕️ Healthcare Provider Dashboard

• Doctor Portal: Specialized dashboard for healthcare providers
• Patient Management: Monitor patient progress and prescribe exercises
• Medical Profiles: Comprehensive health history tracking
• Exercise Prescriptions: Customized workout plans

📱 Cross-Platform Mobile App

• React Native: Runs on both iOS and Android
• Expo Framework: Fast development and deployment
• Camera Integration: Real-time video capture and analysis
• Offline Support: Core features work without internet

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   React Native  │    │   FastAPI       │    │   AI Services   │
│   Mobile App    │◄──►│   Backend       │◄──►│   (Hugging Face)│
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Expo Camera   │    │   SQLite DB     │    │   TensorFlow/   │
│   MediaPipe     │    │   File Storage  │    │   MediaPipe     │
└─────────────────┘    └─────────────────┘    └─────────────────┘

🚀 Quick Start

Prerequisites

• Node.js 16+
• Python 3.8+
• npm/yarn
• iOS/Android development environment

Mobile App Setup

1. Install dependencies:

   npm install
   # or
   yarn install

2. Start the development server:

   npm start
   # or
   yarn start

3. Run on device:

   # iOS
   npm run ios
   # or
   yarn ios
   
   # Android
   npm run android
   # or
   yarn android

Backend Setup

1. Navigate to backend directory:

   cd backend

2. Install Python dependencies:

   pip install -r requirements.txt

3. Start the server:

   python main.py

4. Access API documentation:

   • Interactive docs: http://localhost:8000/docs
   • ReDoc: http://localhost:8000/redoc

📋 Tech Stack

Frontend (React Native)

• React Native: 0.81.4 - Cross-platform mobile development
• React: 19.1.0 - UI component library
• TypeScript: ~5.9.2 - Type-safe JavaScript
• Expo: ~54.0.13 - Development platform
• Expo Camera: Camera access and video capture
• React Native Reanimated: Advanced animations

Backend (Python)

• FastAPI: 0.104.1 - Modern web framework
• SQLite: Embedded database
• JWT Authentication: Secure user authentication
• BCrypt: Password hashing
• Uvicorn: ASGI server

AI & Computer Vision

• MediaPipe: 0.10.7 - Pose estimation
• OpenCV: 4.8.1.78 - Computer vision
• TensorFlow: Machine learning framework
• Hugging Face: Free medical AI models
• NumPy: Numerical computing

🏋️‍♀️ Supported Exercises

Strength Training

• Squat - Lower body strength
• Push Up - Upper body strength
• Hammer Curl - Bicep training
• Core Strengthening - Core stability
• Resistance Band Training

Flexibility & Mobility

• Chair Yoga - Seated yoga poses
• Gentle Stretching - Basic stretching
• Range of Motion - Joint mobility
• Pelvic Tilts - Core flexibility
• Wrist Stretches - Wrist mobility

Balance & Coordination

• Single Leg Balance - Balance training
• Side Step - Lateral movement
• Seated Marching - Seated cardio

Therapeutic Exercises

• Breathing Exercise - Respiratory training
• Pelvic Floor Exercises - Pelvic health
• Tennis Elbow Exercise - Elbow rehabilitation
• Prenatal Yoga - Pregnancy-safe exercises

🤖 AI Health Chatbot

Free Setup (No API Key Required)

The chatbot works out of the box with intelligent fallback responses.

Enhanced Setup (Optional)

1. Create a free Hugging Face account at huggingface.co
2. Generate an API token in Settings > Access Tokens
3. Add to environment configuration:

   // config/environment.ts
   HUGGING_FACE_API_KEY: 'hf_your_token_here'

Available Free Models

• microsoft/DialoGPT-medium - Conversational AI
• microsoft/BioGPT-Large - Medical text generation
• facebook/blenderbot-400M-distill - Alternative conversational AI
• dmis-lab/biobert-base-cased-v1.2 - Medical BERT model

🏥 Healthcare Features

User Types

• Patients: Exercise tracking, health monitoring, AI assistant
• Doctors: Patient management, exercise prescriptions, progress monitoring

Medical Profiles

• Comprehensive health history
• Disease tracking
• Medication management
• Emergency contacts
• Lifestyle factors

Security & Privacy

• JWT token authentication
• Encrypted data transmission
• Local data storage
• HIPAA-compliant design
• No PHI transmission to external services

📊 API Endpoints

Authentication

• POST /auth/register - Register new user
• POST /auth/login - User login
• GET /auth/me - Get current user info

Exercise Analysis

• POST /api/analyze-video - Full video analysis
• POST /api/analyze-frame - Real-time frame analysis
• GET /api/exercise-config/{type} - Exercise configuration

User Management

• GET /users/profile - Get user profile
• PUT /users/profile - Update user profile

🔧 Configuration

Environment Variables

// Development
API_BASE_URL: 'http://localhost:8000'
ENABLE_POSE_ESTIMATION: true
CAMERA_QUALITY: 'medium'
DEBUG_MODE: true

// Production
API_BASE_URL: 'https://api.swaphealth.com'
CAMERA_QUALITY: 'high'
DEBUG_MODE: false

Feature Flags

• POSE_ESTIMATION_V2: Enhanced pose estimation
• ADVANCED_ANALYTICS: Detailed performance metrics
• PROVIDER_DASHBOARD: Healthcare provider features
• AI_HEALTH_CHATBOT: AI assistant functionality

🧪 Testing

Backend Testing

cd backend
python test_endpoints.py

Mobile App Testing

# Unit tests
npm test
# or
yarn test

# Integration tests
npm run test:integration
# or
yarn test:integration

📱 Deployment

Mobile App

• iOS: Build with Xcode and deploy to App Store
• Android: Build APK/AAB and deploy to Google Play Store
• Expo: Use Expo Application Services for automated builds

Backend

• Docker: Containerized deployment
• Cloud Providers: AWS, Google Cloud, Azure
• Local: Direct Python deployment

🔒 Security Considerations

• Change SECRET_KEY in production
• Use HTTPS in production
• Configure CORS for your domain
• Implement rate limiting
• Regular security updates
• Backup database regularly

📖 Documentation

• Setup Guide - Detailed setup instructions
• Tech Stack - Complete technology overview
• Chatbot Setup - AI assistant configuration
• API Documentation - Interactive API docs

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make changes with tests
4. Submit a pull request

📄 License

This project is licensed under the 0BSD License - see the LICENSE file for details.

🆘 Support

Common Issues

Backend Connection Failed

• Verify backend server is running
• Check API_BASE_URL configuration
• Ensure network connectivity

Camera Permissions Denied

• Check iOS Info.plist and Android permissions
• Grant camera permissions in device settings

Video Upload Failed

• Check file size limits (max 100MB)
• Verify video format compatibility
• Check network connection

Pose Analysis Not Working

• Ensure full body is visible in camera
• Check lighting conditions
• Verify MediaPipe installation

Getting Help

1. Check this documentation
2. Review troubleshooting guides
3. Check GitHub issues
4. Contact development team

🎯 Roadmap

• Advanced exercise analytics
• Wearable device integration
• Telemedicine video calls
• Multi-language support
• Offline exercise library
• Social features and challenges
• Integration with health records

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Disclaimer: This application provides general health and fitness information only and should never replace professional medical advice, diagnosis, or treatment. Always consult qualified healthcare providers for medical concerns.

📞 Contact

For questions, support, or contributions, please contact the development team or submit an issue on GitHub.

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Built with ❤️ for better health and fitness outcomes.