POSE: Posture Optimization & Smart Exercise
Link to open source: https://github.com/devcode8/POSE
POSE: Posture Optimization & Smart Exercise
POSE is an AI-powered fitness assistant that monitors and analyzes users' posture during exercise in real-time. It provides instant feedback to enhance performance and minimize the risk of injury.
Key Features
- Real-time Posture Detection: Uses the MediaPipe Pose model to track and analyze user movements.
- Instant Feedback: Provides real-time corrective feedback on exercise form, ensuring proper alignment.
- AI-Driven Optimization: Built on the Fetch.AI ecosystem, leveraging intelligent agents to optimize the user’s fitness routine.
- Seamless Integration: Offers a responsive web interface for user interaction, making it accessible anywhere.
Technologies Used
- Fetch.AI SDK: Powers the backend agents for intelligent analysis and feedback.
- MediaPipe: Used for real-time pose estimation and movement tracking.
- Flask: Backend server framework for handling requests and communicating with the AI model.
- React.js: Frontend framework for building an interactive and responsive web interface.
- Python: Core programming language used for AI modeling, backend services, and integration with MediaPipe.
How it Works
- Pose Detection: The MediaPipe Pose model detects and tracks key body points as users perform exercises.
- Feedback Mechanism: Data is sent to the Fetch.AI agents, which analyze the user’s posture and provide feedback through the Flask server.
- User Interface: React.js provides a clean and responsive interface for users to receive posture feedback and view their exercise progress.
This build was uploaded as a hackathon project
