Cognitive Training App Personalization via Biosignal Feedback
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Solution Overview
Problem
As the aging society progresses, there is a growing need for effective methods to prevent and improve dementia symptoms, particularly in individuals with mild cognitive impairment, as existing training methods lack personalized and adaptive approaches to optimize cognitive function training based on user-specific data and environmental factors.
Innovation Solution
A method and device for controlling a cognitive function training app that determines user inputs, optimizes training sessions in real-time based on biosignal data, circadian rhythms, and environmental factors, adjusting training speed and duration to provide personalized and adaptive cognitive function training through a terminal device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cognitive function training is provided using general methods, then training can be delivered to users, but the training cannot be optimized for individual user needs and conditions
Solution Approach 1:
The system collects user information in advance (sleep patterns, circadian rhythm, schedule, activity level, depression level) before providing training, allowing it to pre-optimize training parameters tailored to each user's individual conditions and needs
Solution Approach 2:
The training program dynamically adjusts its parameters (training time, speed, duration, content) based on real-time monitoring of user inputs and collected information, transforming a static program into an adaptive system that responds to user state changes
2Productivity
If training is provided without considering user inputs and conditions, then the system remains simple, but training effectiveness and efficiency are reduced
Solution Approach 1:
The system continuously monitors user inputs during training (voice inputs, responses) and uses this feedback to adjust training parameters in real-time, optimizing training efficiency by adapting to the user's current cognitive state and performance
Solution Approach 2:
The system automatically analyzes collected user information and adjusts training parameters without requiring manual intervention from trainers or users, enabling the training program to self-optimize based on accumulated data about user patterns and responses
3Adaptability or versatility
If the app does not monitor user state in real-time, then the system is simpler to operate, but it cannot adapt to changing user conditions during training
Solution Approach 1:
The system automatically monitors user state through various sensors and input mechanisms, and self-adjusts training parameters without requiring user intervention or complex manual controls, maintaining ease of operation while achieving real-time adaptation
Solution Approach 2:
The system replaces manual monitoring and adjustment mechanisms with automated sensor-based detection and algorithmic parameter optimization, eliminating the need for complex operational procedures while enabling continuous real-time adaptation to user conditions
Data Source
AI summary
Provided is a method of controlling an improved cognitive function training app, the method including determining whether the cognitive function training app has been initiated by an input from a user to a terminal, optimizing cognitive function training provided by the cognitive function training app to be appropriate for the user, based on a result of the determining of whether the cognitive function training app has been initiated, and information of the user of the terminal, and based on the cognitive function training app being initiated or resumed by an input from the user, providing the optimized cognitive function training through the terminal.