Fitness Posture Guidance Using Expert Motion Angle Ranges
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Solution Overview
Problem
Current fitness applications fail to accurately assess the correctness of user's exercise motion, leading to reduced fitness effectiveness and inability to calculate caloric expenditure accurately.
Innovation Solution
A fitness posture guidance system and method that uses a server device and user terminal device to analyze real-time video streams, comparing user postures against a generated final motion model based on expert and general user data to provide timely posture guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current fitness applications only record exercise duration, then the system complexity is low, but the measurement precision of fitness posture correctness is insufficient
Solution Approach 1:
The patent introduces an intermediary server device that receives video streams from the user terminal, extracts posture data, compares it with the motion model, and provides assessment results. This intermediary architecture allows the user terminal to remain relatively simple while achieving precise posture measurement through the server's processing capabilities.
Solution Approach 2:
The patent replaces traditional mechanical movement sensors with image capture devices (cameras) that capture visual data. The posture assessment is achieved through image processing and computational algorithms rather than direct mechanical measurement, enabling precise posture detection with simpler hardware.
2Ease of operation
If users exercise without professional coaching, then the ease of operation is improved, but the reliability of fitness effect is reduced
Solution Approach 1:
The system enables users to perform fitness exercises at home without professional coaches by providing automated real-time posture guidance. The application captures user movements, compares them against expert motion models, and provides immediate feedback, allowing users to self-monitor and self-correct their form throughout the exercise routine.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors user posture during exercise, compares it with the target motion model, and provides real-time guidance. This closed-loop feedback allows users to adjust their movements dynamically, ensuring correct form and maximizing fitness effectiveness without professional supervision.
3Productivity
If real-time posture guidance is provided, then the productivity of fitness exercise is improved, but the use of energy by the system increases
Solution Approach 1:
The system employs periodic action by capturing video streams at specific intervals rather than continuously processing every pixel in real-time. The server extracts posture data at key moments during the exercise routine, providing guidance when needed while reducing overall computational load and energy consumption compared to continuous real-time analysis.
Data Source
AI summary
A fitness posture guidance method and a fitness posture guidance system are provided. A setting of a plurality of target fitness postures and one attention part of a target fitness action is received. A plurality of target frames respectively corresponding to the target fitness postures are obtained from an expert video according to a plurality of marked times. A professional angle range of the attention part of each of the target fitness postures is obtained based on a plurality of body feature points of each of the target frames to generate an expert motion model. The expert motion model is integrated with an application motion model to generate a final motion model including a final angle range of the attention part of each of the target fitness postures. A prompt function is executed according to the final motion model and multiple body postures in a real-time video stream.