Mobile Exercise Trajectory Analysis for Real-Time Posture Feedback
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Solution Overview
Problem
Existing sport assistance systems are costly and require professional coaching, making them impractical for individual users, and lack widespread adoption due to high construction costs and limited data-driven feedback for non-professional exercisers.
Innovation Solution
A dynamic trajectory analysis system using computer vision, edge AI, and machine learning on a smart mobile device for real-time recording and analysis of exercise posture, providing immediate feedback and optimization suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If professional sport assistance systems are used, then measurement precision and analysis accuracy are improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses image copying technology to capture and analyze exercise posture through 2D images, creating a simplified digital representation that eliminates the need for complex 3D sensing equipment while maintaining sufficient analysis accuracy for individual exercisers
Solution Approach 2:
The patent replaces complex mechanical sensing systems with computer vision and AI algorithms, using software-based image processing to achieve posture analysis without expensive hardware infrastructure
2Manufacturing precision
If professional coaching assistance is provided, then exercise optimization quality is improved, but ease of operation and accessibility deteriorate
Solution Approach 1:
The system enables exercisers to independently capture their own posture images, perform self-analysis using the AI model, and receive automated feedback without requiring professional coaches to operate the equipment or interpret data
Solution Approach 2:
The system provides automated real-time feedback on exercise posture through image analysis, delivering optimization suggestions directly to users without requiring professional coach intervention, thus maintaining accessibility while preserving quality guidance
3Productivity
If real-time posture analysis is implemented, then productivity and feedback speed are improved, but use of energy and computational resources increase
Solution Approach 1:
The system performs partial analysis by focusing only on key posture points and critical exercise parameters rather than analyzing every detail, reducing computational energy requirements while maintaining useful feedback speed for exercise optimization
Data Source
AI summary
The method for using a dynamic trajectory analysis system for an exerciser uses technologies such as computer vision, edge artificial intelligence (AI), machine learning, and human factors engineering, in conjunction with a smart mobile communication device to perform the following: automatically capturing and recording images of posture of the exerciser during the exercise process; and further analyzing a sport event, sport behavior, and sport equipment in the images, and then obtaining a key information for providing assistance in optimizing the exercise process. The method uses edge AI models to achieve real-time prediction of objective physical performance of objects such as a human body, sport equipment, and a ball in a real environment. A prediction result is presented in a data format and visualized manner, providing a user with a real-time feedback and analysis information.