Kinetic Lab - Precision Kineticism

A high-performance posture analysis application for gym-goers and Hyrox athletes. Uses AI computer vision to analyze biomechanics in real-time and provide personalized coaching.

Features

• Real-time Pose Estimation: Uses TensorFlow.js and MoveNet for accurate joint tracking
• Multi-Pose Analysis: Analyze multiple athletes during group workouts
• Personalized Coaching: Get real-time feedback on form and technique
• Performance Analytics: Track progress over time with detailed metrics
• Exercise Library: Curated exercises with difficulty levels and categories
• Session Reports: Comprehensive analysis of each workout session

Tech Stack

Frontend

• React 18 with TypeScript
• Vite for fast development
• Tailwind CSS for styling
• TensorFlow.js + MoveNet for pose estimation
• React Router for navigation

Backend

• Node.js with Express
• PostgreSQL (setup ready)
• CORS support for API requests

Setup

Prerequisites

• Node.js 18+
• npm or yarn

Installation

1. Clone and navigate to the project:

cd smartGym

2. Install dependencies:

npm install

3. Create environment file:

cp .env.example .env

4. Update .env with your configuration

Running the App

Development Mode (Frontend only)

npm run dev

The app will be available at http://localhost:5173

Development Mode (Frontend + Backend)

npm run dev:all

Production Build

npm run build
npm run preview

Backend Only

npm run server

The API will be available at http://localhost:5000

Project Structure

smartGym/
├── src/
│   ├── components/        # Reusable UI components
│   ├── pages/            # Page components (Dashboard, LiveCapture, etc.)
│   ├── App.tsx           # Main app component with routing
│   ├── main.tsx          # Entry point
│   └── index.css         # Global styles
├── server/
│   └── index.js          # Express server
├── KineticLab/           # Design files and mockups
├── tailwind.config.js    # Tailwind configuration
├── vite.config.ts        # Vite configuration
└── package.json          # Dependencies

Pages

• Dashboard: Home page with quick access to recent sessions and favorite exercises
• Live Capture: Real-time video analysis with pose estimation
• Exercise Selection: Browse and select exercises from the library
• Session Report: Detailed analysis of completed workout sessions
• Training History: View past sessions and track progress

Design System

The app follows the "Precision Kineticism" design aesthetic with:

• High-contrast dark theme (#0d0f0f background)
• Electric lime primary accent (#cffc00)
• Orange secondary for warnings (#ff734a)
• Typography: Lexend (headlines), Manrope (body), Space Grotesk (data labels)
• No-line UI principle with depth via tonal shifts

Backend API Endpoints

• GET /api/health - Health check
• GET /api/sessions - Get all sessions
• GET /api/exercises - Get exercise library
• POST /api/analysis - Analyze pose keypoints

Future Enhancements

• PostgreSQL database integration for persistent data storage
• User authentication and profiles
• Advanced pose analysis with ML models
• Real-time multi-user tracking
• Mobile app version
• Cloud sync and backup

Contributing

To contribute:

1. Follow the design system guidelines
2. Use TypeScript for type safety
3. Keep components reusable and focused
4. Test on mobile devices

License

MIT