Interactive teaching evaluation auxiliary system and device based on multi-modal fusion

By constructing a user training motion profile database and a real-time evaluation and feedback mechanism, the problems of one-sided motion evaluation and lack of precision in guidance in traditional physical education teaching have been solved, enabling accurate recommendation of personalized programs and continuous optimization of movements.

CN120807242BActive Publication Date: 2026-01-13MAILEFENG (XIAMEN) E-COMMERCE CO LTD
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Patent Information

Application Number
CN202511249695.1
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-09-03
Publication Date
2026-01-13
Estimated Expiration
2045-09-03

AI Technical Summary

Technical Problem

Traditional physical education classroom teaching models struggle to quantify, record, and systematically analyze students' movement standardization and training intensity. Personalized teaching goals are difficult to implement, and the lack of a multimodal data fusion assessment system and personalized program matching mechanism leads to a one-sided portrayal of athletic ability and a lack of precise guidance.

Method used

The interactive teaching assessment assistance system based on multimodal fusion constructs a user training action profile library through the profile module, generates the optimal guidance plan in combination with the strategy recommendation module, evaluates the actions in real time and provides feedback on the spatiotemporal change chain of non-standard actions through the auxiliary adjustment module, and makes real-time adjustments through the source tracing feedback module, forming a closed-loop optimization.

Benefits of technology

It enables accurate assessment of multimodal data and personalized solution matching, improves the scientific nature and interactivity of assessment assistance, shortens the movement correction cycle, and enhances the scientific nature and effectiveness of training.

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Abstract

The application belongs to the field of evaluation assistance, and particularly relates to an interactive teaching evaluation assistance system and device based on multi-modal fusion. The system collects multi-dimensional information through a portrait module, combines multi-modal feature extraction and a knowledge graph algorithm to construct a user training action portrait library. A strategy recommendation module generates an optimal guidance scheme from a portrait library, real-time information and a teaching guidance strategy library through a correction scheme matching model. An auxiliary adjustment module collects training action images in real time, uses a space-time feature extraction model and an evaluation algorithm to obtain a continuous correction action sequence and a standard score after guidance. A traceability feedback module combines an action standard knowledge base, obtains a horizontal and vertical space-time change chain of non-standard actions through a forward reasoning model, and feeds back to the instructor to adjust the scheme in real time until the action meets the standard. The application realizes precise evaluation and personalized scheme matching of multi-modal data fusion, and effectively improves the scientificity and interactivity of evaluation assistance.
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