Brain-Mimicking AI Model for Meta-Memory Mental Health Profiling
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Solution Overview
Problem
Existing mental health monitoring technologies struggle to accurately assess cognitive decline and metacognition, leading to reduced explanatory power in complex situations, and lack comprehensive mental health profiling capabilities.
Innovation Solution
A mental health measuring device using a brain mimicking artificial intelligence model to analyze user performance in meta memory games, optimizing parameters to estimate cognitive behavior values and provide individual brain function values, enabling accurate mental health profiling and risk prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional speech pattern analysis is used to assess mental health, then the system is simple to operate, but the measurement precision of cognitive decline is insufficient
Solution Approach 1:
The patent introduces a meta-memory game as an intermediary tool between the user and the cognitive assessment system. The game serves as a mediator that translates complex cognitive functions into measurable gameplay data, enabling precise assessment of memory recall, inference, and metacognition without requiring direct complex medical testing procedures
Solution Approach 2:
The patent replaces traditional mechanical speech analysis methods with a digital game-based assessment system. The mechanical system of speech pattern recognition is substituted with an electronic game platform that collects behavioral data, thereby improving measurement precision while maintaining ease of operation through familiar digital interfaces
2Reliability
If metacognition measurement is not implemented, then the device complexity is reduced, but the reliability of mental health risk prediction deteriorates
Solution Approach 1:
The patent segments the cognitive assessment into distinct measurable components: memory recall accuracy, inference accuracy, learning accuracy, and strategic decision-making bias. By dividing metacognition into these separable elements, the system can measure each component independently through specific game mechanics, thereby improving prediction reliability without overwhelming system complexity
Solution Approach 2:
The patent implements feedback mechanisms within the meta-memory game that provide real-time information about user performance in memory recall, inference, and decision-making tasks. This feedback loop enables the system to continuously refine its assessment of metacognition and mental health risks, improving prediction reliability through adaptive measurement
3Adaptability or versatility
If a comprehensive cognitive model including metacognition is used, then the explanatory power in complex situations is improved, but the device complexity increases
Solution Approach 1:
The patent designs the meta-memory game to serve multiple cognitive assessment functions simultaneously. A single game platform measures memory recall, inference capability, learning processes, and metacognitive strategies, thereby achieving comprehensive explanatory power for complex cognitive situations without requiring separate specialized systems for each function
Solution Approach 2:
The patent merges multiple cognitive assessment tasks into a unified meta-memory game framework. By combining memory tasks, inference tasks, and metacognitive evaluation into a single integrated game system, the patent achieves comprehensive cognitive modeling while managing complexity through unified game mechanics and centralized data collection
Data Source
AI summary
An artificial intelligence device according to an embodiment of the present disclosure comprises a memory configured to store a brain-mimicking artificial intelligence model learned through a reinforcement learning; a mental health measuring device configured to collect subject data including a value of a memory recall confidence, a memory recall accuracy, a value of an inference confidence, an inference accuracy, a learning accuracy, and a strategic decision-making bias according to a user's performance of a meta memory game; and a processor configured to: obtain a plurality of cognitive behavior values from the subject data using the brain mimicking artificial intelligence model, obtain a plurality of brain function estimation signals corresponding to each of the plurality of cognitive behavior values, and map each of the plurality of brain function estimation signals to a brain signal corresponding to a specific brain function.