• Overview
• Key Features
• Technology Stack
• Architecture
• Installation & Setup
• Configuration
• Project Structure
• Usage Guide
• Development
• Contributing
• License

Muscle Intelligence is a sophisticated mobile fitness application designed to revolutionize how users approach their workouts. By combining advanced computer vision algorithms with machine learning models, the app provides real-time feedback on exercise form, identifies muscle groups being targeted, and helps users optimize their training routines while minimizing injury risk.

• Real-Time Form Analysis: Get instant feedback on your exercise technique using advanced pose estimation
• Muscle Group Identification: Automatically detect which muscle groups are being targeted during exercises
• Visual Feedback: Color-coded analysis showing perfect areas, areas needing work, and potential danger zones
• Comprehensive Tracking: Monitor workout history, progress, and body areas targeted over time
• Professional-Grade: Built with modern mobile development best practices and scalable architecture

• Upload & Analyze: Upload workout videos from your device library
• Real-Time Recording: Record exercises directly through the app's camera interface
• Skeleton Detection: Advanced pose estimation with visual skeleton overlay
• Form Scoring: Get detailed feedback on exercise form with color-coded indicators:
  • 🟢 Green: Perfect form areas
  • 🟠 Orange: Areas needing improvement
  • 🔴 Red: Danger zones requiring attention

• Workout History: Comprehensive log of all analyzed workouts
• Body Areas Targeted: Visual breakdown of muscle groups worked over time
• Progress Analytics: Track improvements in form and consistency
• Exercise Library: Browse and learn about different exercises

• Secure Authentication: Powered by Clerk for enterprise-grade security
• User Profiles: Personalized profiles with workout statistics
• Theme Support: Light and dark mode for comfortable viewing
• Device Management: Track and manage connected fitness devices

• Feed: Share progress and achievements with friends
• Community: Connect with other fitness enthusiasts

• React Native 0.75.3 - Cross-platform mobile framework
• Expo 51.0.32 - Development platform and toolchain
• React Navigation 6.x - Navigation library (Stack, Bottom Tabs)
• React Native Reanimated 3.15.3 - Smooth animations
• React Native Gesture Handler 2.20.0 - Touch gesture handling

• Firebase 10.14.1 - Backend-as-a-Service
  • Firestore - NoSQL database
  • Firebase Storage - Video and media storage
  • Firebase Authentication (via Clerk integration)
• Clerk 2.2.16 - Authentication and user management

• Expo Camera 15.0.16 - Camera access and video recording
• Expo Image Picker 15.0.7 - Image and video selection
• Expo AV 14.0.7 - Audio/video playback
• React Native Video 6.6.4 - Video player component

• TensorFlow.js (via ML Playground) - Machine learning models
• Pose Estimation Models - Human pose detection
• Three.js 0.168.0 - 3D graphics and visualization
• Expo GL 14.0.2 - WebGL rendering

• TypeScript (partial) - Type safety
• ESLint - Code linting
• Metro Bundler - React Native bundler

┌─────────────────────────────────────────┐
│         Navigation Container            │
├─────────────────────────────────────────┤
│  ┌──────────────┐  ┌─────────────────┐ │
│  │  Auth Stack  │  │  Main App Tabs  │ │
│  │              │  │                 │ │
│  │ • Login      │  │ • Home          │ │
│  │ • Signup     │  │ • Record        │ │
│  │ • Verify     │  │ • Upload        │ │
│  └──────────────┘  │ • Profile       │ │
│                    └─────────────────┘ │
└─────────────────────────────────────────┘

1. User Authentication: Clerk handles authentication → Firebase stores user data
2. Video Upload: User selects/records video → Uploaded to Firebase Storage
3. Analysis Pipeline: Video processed → ML models analyze form → Results stored in Firestore
4. Feedback Display: Analysis results → Visual feedback with skeleton overlay → User insights

• Authentication Layer: Clerk provider wrapping the entire app
• Navigation: Stack navigators for auth, upload flow, and profile sections
• State Management: React hooks and context (ThemeContext)
• Media Processing: Expo Camera and Image Picker for capture/selection
• ML Integration: ML playground models for pose estimation and form analysis

• Node.js >= 18.x
• npm, yarn, or pnpm (project uses pnpm)
• Expo CLI (install globally: npm install -g expo-cli)
• iOS Development: Xcode 14+ (for iOS builds)
• Android Development: Android Studio with Android SDK (for Android builds)
• Firebase Account: For backend services
• Clerk Account: For authentication

git clone <repository-url>
cd Muscle-Intelligence

# Using pnpm (recommended)
pnpm install

# Or using npm
npm install

# Or using yarn
yarn install

Create a .env file in the root directory:

EXPO_PUBLIC_CLERK_PUBLISHABLE_KEY=your_clerk_publishable_key
FIREBASE_API_KEY=your_firebase_api_key
FIREBASE_AUTH_DOMAIN=your_firebase_auth_domain
FIREBASE_PROJECT_ID=your_firebase_project_id
FIREBASE_STORAGE_BUCKET=your_firebase_storage_bucket
FIREBASE_MESSAGING_SENDER_ID=your_firebase_messaging_sender_id
FIREBASE_APP_ID=your_firebase_app_id

1. Create a Firebase project at Firebase Console
2. Enable Firestore Database
3. Enable Firebase Storage
4. Update firebase/firebaseConfig.js with your Firebase credentials
5. Deploy Firestore rules from firestore.rules
6. Deploy Firestore indexes from firestore.indexes.json

1. Create a Clerk account at Clerk
2. Create a new application
3. Copy your publishable key to .env
4. Configure authentication methods (Email, Social, etc.)

cd ios
pod install
cd ..

# Start Expo development server
npm start
# or
pnpm start
# or
yarn start

• iOS: Press i in the terminal or scan QR code with Expo Go app
• Android: Press a in the terminal or scan QR code with Expo Go app
• Web: Press w in the terminal

{
  "expo": {
    "name": "muscle-intelligence",
    "slug": "muscle-intelligence",
    "version": "1.0.0",
    "orientation": "portrait",
    "ios": {
      "bundleIdentifier": "com.yourcompany.muscleintelligence"
    },
    "android": {
      "package": "com.yourcompany.muscleintelligence"
    }
  }
}

Update firebase/firebaseConfig.js with your Firebase project credentials.

The app uses React Navigation with:

• Bottom Tab Navigator: Main app navigation (Home, Record, Upload, Profile)
• Stack Navigators:
  • Auth Stack (Login, Signup, Verification)
  • Upload Stack (Upload flows for different analysis types)
  • Profile Stack (Profile and sub-screens)

Muscle-Intelligence/
├── android/                 # Android native code
│   ├── app/
│   └── build.gradle
├── ios/                     # iOS native code
│   ├── postureAI/
│   └── Podfile
├── assets/                  # Static assets (images, videos, GIFs)
│   ├── *.gif               # Exercise demonstration GIFs
│   └── *.jpg               # Icons and images
├── firebase/                # Firebase configuration
│   ├── firebaseConfig.js   # Firebase initialization
│   ├── firestore.js        # Firestore utilities
│   └── firebaseStorage.js  # Storage utilities
├── hooks/                   # Custom React hooks
│   └── useProtectedRoute.js
├── ml_playground/           # ML models and playground
│   └── posts_code/         # Pose estimation models
├── screens/                 # Application screens
│   ├── auth/               # Authentication screens
│   │   ├── LoginScreen.js
│   │   ├── SignupScreen.js
│   │   └── VerificationScreen.js
│   ├── home/               # Home feed
│   │   └── HomeScreen.js
│   ├── record/             # Video recording
│   │   └── RecordScreen.js
│   ├── upload/             # Video upload and analysis
│   │   ├── UploadBetta.js
│   │   ├── UploadAlpha.js
│   │   ├── UploadGamma.js
│   │   ├── LoadingBettaOne.js
│   │   ├── LoadingBettaTwo.js
│   │   ├── LoadingAlphaOne.js
│   │   ├── LoadingAlphaTwo.js
│   │   ├── SkeletonBetta.js
│   │   ├── SkeletonAlpha.js
│   │   ├── FinalBetta.js
│   │   ├── FinalAlpha.js
│   │   └── StasSample.js
│   ├── profile/             # User profile and settings
│   │   ├── ProfileScreen.js
│   │   ├── WorkoutHistoryScreen.js
│   │   ├── BodyAreasTargetedScreen.js
│   │   ├── ProgressScreen.js
│   │   ├── SettingsScreen.js
│   │   ├── DevicesConnectedScreen.js
│   │   └── ThemeContext.js
│   ├── Button.js
│   ├── ExerciseLibraryScreen.js
│   ├── OnboardingScreen.js
│   ├── PostureAnalysisScreen.js
│   └── ProtectedScreen.js
├── App.js                   # Main application entry point
├── app.config.js           # Expo configuration
├── app.json                # App metadata
├── config.json             # Additional configuration
├── package.json            # Dependencies and scripts
├── firestore.rules         # Firestore security rules
└── firestore.indexes.json  # Firestore indexes

1. Sign Up/Login: Create an account or sign in using Clerk authentication
2. Onboarding: Complete the initial setup process
3. Grant Permissions: Allow camera and storage access when prompted

1. Navigate to the Record tab
2. Tap the camera button to start recording
3. Position yourself in frame
4. Perform your exercise
5. Stop recording when finished
6. The video will be automatically analyzed

1. Navigate to the Upload tab
2. Tap "Upload Video"
3. Select a video from your device library
4. Wait for processing (video is converted to GIF format)
5. View the analysis results with:
   • Skeleton overlay showing pose detection
   • Color-coded feedback on form
   • Muscle groups targeted
   • Areas needing improvement

1. Navigate to Profile tab
2. Access:
   • Workout History: View all past workouts
   • Body Areas Targeted: See muscle group breakdown
   • Progress: Track improvements over time
   • Settings: Customize app preferences

• 🟢 Green Areas: Perfect form - keep doing what you're doing!
• 🟠 Orange Areas: Needs work - focus on improving technique
• 🔴 Red Areas: Danger zone - incorrect form that could lead to injury

# Start development server
npm start

# Run on iOS simulator
npm run ios

# Run on Android emulator
npm run android

# Run on web
npm run web

• Follow React Native best practices
• Use functional components with hooks
• Maintain consistent naming conventions
• Add comments for complex logic

1. Create feature branch: git checkout -b feature/your-feature
2. Implement changes following existing patterns
3. Test on both iOS and Android
4. Update documentation if needed
5. Submit pull request

# Run tests (when test suite is added)
npm test

# Build iOS
expo build:ios

# Build Android
expo build:android

# Or use EAS Build
eas build --platform ios
eas build --platform android

We welcome contributions! Please follow these steps:

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

• Write clear, descriptive commit messages
• Follow the existing code style
• Add tests for new features
• Update documentation as needed
• Ensure all tests pass before submitting

This project is private and proprietary. All rights reserved.

• React Native Documentation
• Expo Documentation
• Firebase Documentation
• Clerk Documentation
• React Navigation

For issues, questions, or contributions, please open an issue on the repository or contact the development team.

• Real-time form analysis during recording
• Exercise recommendations based on progress
• Social sharing and community features
• Integration with fitness wearables
• Advanced analytics and insights
• Custom workout plan generation
• Multi-exercise analysis in single session
• Export workout data
• Integration with popular fitness apps