User-Terminal Cognitive Training with Phased Domain Assessment
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Solution Overview
Problem
The increasing prevalence of dementia and cognitive impairment in aging societies poses a significant challenge, with existing training methods being inadequate for effectively alleviating symptoms, particularly in patients with mild cognitive impairment.
Innovation Solution
A digital dementia therapeutic system utilizing a user terminal that implements a structured training program comprising multiple domain-specific algorithms, including attention, associative, and integrative skills training, with phased execution and assessment, to enhance cognitive function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional training methods are used for cognitive impairment, then the training program is simple to implement, but the training effectiveness is insufficient to alleviate dementia symptoms
Solution Approach 1:
The training program is divided into multiple phases (first phase with first domain training algorithm, second phase with second domain training algorithm) that are executed sequentially. Each phase contains specific training algorithms tailored to different cognitive domains, allowing the system to progressively build cognitive skills while managing complexity through structured progression.
Solution Approach 2:
The system dynamically adjusts the training program based on user progress and performance. The controller determines whether to execute the first or second phase based on assessment results, and the training algorithms adapt to individual user needs. This dynamic adjustment maintains effectiveness while managing complexity through intelligent control rather than fixed rigid structures.
2Reliability
If multiple domain training algorithms are implemented, then cognitive function improvement is enhanced, but the system complexity increases
Solution Approach 1:
The training system segments cognitive training into distinct domains (attention, associative, integrative skills) with dedicated algorithms for each. The first domain training algorithm addresses attention, the second addresses associative skills, and the third addresses integrative skills. This segmentation allows complex cognitive functions to be trained through manageable, specialized modules rather than a monolithic complex system.
Solution Approach 2:
The user terminal serves multiple functions: it displays training algorithms, collects user inputs, assesses training results, and provides visual indications. The controller manages multiple training phases and algorithms through a single integrated system. This multi-functionality reduces overall system complexity by consolidating components rather than requiring separate systems for each function.
3Measurement precision
If phased execution with assessment is implemented, then training precision is improved, but the time required for training increases
Solution Approach 1:
The system incorporates assessment mechanisms that evaluate user performance after each training phase and provide feedback to the controller. Based on assessment results, the controller determines whether to proceed to the next phase or repeat the current one. This feedback loop ensures precise measurement of training effectiveness while optimizing time by avoiding unnecessary repetition of ineffective training sequences.
Solution Approach 2:
The system performs preliminary assessments to determine which training phase the user should undertake first. By evaluating user baseline skills before beginning training, the system can skip unnecessary phases or start with appropriate difficulty levels, reducing overall training time while maintaining assessment precision through targeted evaluation at key decision points.
Data Source
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AI summary
Provided is a method of alleviating cognitive impairment based on a user terminal, the method including performing control, in response to a first input to a user terminal, such that a first domain training algorithm, a second domain training algorithm, and a third domain training algorithm of a first phase are output on the user terminal, determining, based on second inputs to the user terminal, whether the first domain training algorithm, the second domain training algorithm, and the third domain training algorithm of the first phase are completed, and determining, based on a result of the determining, whether the first phase is normally terminated, performing control, after the first phase is terminated and in response to a third input to the user terminal, such that a first domain training algorithm, a second domain training algorithm, and a third domain training algorithm of a second phase are output on the user terminal, determining, based on fourth inputs to the user terminal, whether the first domain training algorithm, the second domain training algorithm, and the third domain training algorithm of the second phase are completed, and determining, based on a result of the determining, whether the second phase is normally terminated, and performing control, based on whether the first phase and the second phase are terminated, such that a first visual indication is output on the user terminal.