Personalized virtual-real interactive cognitive game system based on ai adaptive brain cognitive enhancement

The AI-adaptive personalized virtual-real interactive cognitive game system dynamically adjusts the game difficulty and provides personalized feedback, solving the problems of insufficient systematicity and adaptability of traditional cognitive training methods and improving the cognitive skills training effect of teenagers.

CN120437574BActive Publication Date: 2025-11-25BEIJING PUJU HEALTH TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202510939781.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-07-08
Publication Date
2025-11-25
Estimated Expiration
2045-07-08

AI Technical Summary

Technical Problem

Traditional cognitive training methods lack systematic design, cannot provide personalized feedback, and are difficult to adapt to the different cognitive levels and psychological states of players, resulting in low interest and participation in cognitive training among teenagers.

Method used

This personalized virtual-real interactive cognitive game system, which employs AI adaptive brain cognition enhancement, provides a personalized cognitive training experience through structured task design, a graded difficulty system, and a standardized evaluation mechanism, combined with the principles of cognitive psychology. It utilizes dynamic difficulty adjustment algorithms, real-time feedback, and data tracking analysis.

Benefits of technology

The game difficulty is dynamically adjusted, and personalized feedback is provided to improve teenagers' attention, memory, executive function, and perception, thereby enhancing training effectiveness and increasing player engagement and training results.

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Abstract

The application discloses a personalized virtual-real interaction cognitive game system based on AI adaptive brain cognitive enhancement, comprising: a cognitive game design module for designing multiple cognitive tasks corresponding to attention, memory, executive function and perception function based on a dynamic difficulty adjustment algorithm according to user characteristics; the dynamic difficulty adjustment algorithm is used for dynamically adjusting the difficulty of a specific level task according to the behavior state and psychological state of the user; a cognitive task guiding module interacts with the user through a multi-modal guiding mechanism to guide the user to complete the cognitive task; a data tracking and analysis module is used for recording the performance and growth trajectory of the user in the completion process of each cognitive task; an instant feedback module provides feedback based on an instant feedback generation algorithm; a cognitive ability evaluation report module is used for generating a corresponding cognitive ability evaluation report according to the performance and data tracking and analysis algorithm; and a data storage module is used for storing the behavior data, emotion record and cognitive ability evaluation report of the user.
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