Inspiration
As someone passionate about fitness and technology, I wanted to solve a common problem many face during workouts: improper form and posture. Poor form not only slows progress but also leads to injuries. I envisioned a mobile-first AI coach that could give real-time feedback and personalized corrections—without needing bulky equipment or expensive trainers. That vision became FitBuddy.
What it does
FitBuddy is an AI-powered fitness coach that helps users master proper form using only their smartphone camera. It uses real-time pose detection to:
Track and score reps based on form quality
Detect posture imbalances (left–right / front–back)
Give instant visual and spoken feedback
Generate adaptive workout plans
Count reps and track progress
Provide habit coaching and injury-risk alerts
All of this happens on-device, keeping the experience seamless and private—no sensors or wearables required.
How I built it
I built FitBuddy using:
React Native with Expo for cross-platform mobile development
TensorFlow.js and Blazepose models for real-time pose detection
React Native Reanimated for smooth UI feedback animations
AsyncStorage for storing user preferences and progress locally
Expo Camera for accessing the front-facing camera
Lucide Icons and Linear Gradients for a modern, vibrant UI
TypeScript for robust typing and maintainability
The architecture is modular, with reusable components for the camera view, heatmaps, rep tracking, analytics, and more.
Challenges I ran into
Fine-tuning pose detection for varying body types and lighting conditions
Preventing frame drops during high-load computation (real-time detection)
Designing an interface that conveys complex feedback in a clear, motivating way
Managing app state and camera permissions smoothly on both iOS and Android
Syncing motion logic with animations while keeping performance high
Accomplishments that I'm proud of
Creating a completely sensor-free fitness tracking experience
Developing real-time rep quality scoring and imbalance detection
Designing a sleek, motivational UI that's beginner-friendly yet powerful
Achieving on-device analysis for privacy and responsiveness
Building the full project solo from scratch
What I learned
Advanced animation techniques using Reanimated and shared values
Managing local data with AsyncStorage in a clean and reactive way
Performance optimization for on-device ML models in mobile apps
UI/UX best practices for fitness applications
Adapting open-source pose models to custom use cases
What's next for FitBuddy: AI Fitness Coach & Form Tracker
Cloud sync and personalized insights via a backend (e.g., Supabase or Firebase)
More exercise types and custom workout creation
A voice assistant that guides workouts hands-free
Leaderboards, challenges, and community engagement features
Offline capabilities for workouts without an internet connection
Built With
- asyncstorage
- built-with:-react-native
- expo-lineargradient
- expo.io
- gemini
- lucide-icons
- react
- react-native-reanimated
- tensorflow.js-(blazepose)
- typescript
- vision-camera
- youtube
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