A method and system for dynamically generating training plans and scoring movement quality with smart dumbbells.

By collecting motion data through the built-in sensors of smart dumbbells and combining it with personalized parameters and historical records, a dynamic training plan and scoring model are constructed. This solves the problems of dynamic adaptability and motion quality assessment in smart dumbbell systems, and improves the personalization and safety of training plans.

CN120586366BActive Publication Date: 2025-11-14ZHUHAI YUNMAI TECH CO LTD
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Patent Information

Application Number
CN202511107689.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-08-08
Publication Date
2025-11-14
Estimated Expiration
2045-08-08

AI Technical Summary

Technical Problem

Existing smart dumbbell systems lack dynamic adaptability and cannot perceive changes in the user's physical fitness and the standardization of movements in real time during training. This results in a mismatch between training intensity and the user's actual ability, and the means of assessing movement quality are limited, making it difficult to accurately assess and adjust training plans.

Method used

By collecting motion data in real time through the built-in accelerometer, angular velocity sensor, and pressure sensor of the smart dumbbell, and combining it with the user's personalized parameters and historical training records, a dynamic training plan generation algorithm module and a motion quality scoring model are constructed to achieve multi-dimensional motion quality scoring and closed-loop feedback adjustment.

Benefits of technology

It enables dynamic adjustment of intelligent dumbbell training plans, accurately assesses movement quality, improves the personalization and safety of training effects, reduces the risk of sports injuries, and adapts to the individual differences of different users.

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Abstract

This application relates to the field of intelligent fitness equipment and sports training control technology, and provides a method and system for dynamically generating training plans and scoring movement quality using intelligent dumbbells. The method utilizes the accelerometer, angular velocity sensor, and pressure sensor built into the intelligent dumbbell to collect real-time movement data and personalized parameters input by the user during training. The movement data and personalized parameters are input into a preset training plan generation algorithm module to generate a phased training plan that includes movement type, training duration for each set, rest intervals, and weight adjustment strategies. A movement quality scoring model is constructed, which pre-stores standard movement templates. These templates include standard trajectory curves, speed threshold ranges, amplitude baselines, and force symmetry parameters corresponding to different training movements. The movement data is then matched and analyzed against the standard movement templates in multiple dimensions, and the score is dynamically adjusted based on the user's current fatigue level.
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