Cognitive Training System Using AI for Personalized Risk Prediction
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Solution Overview
Problem
Current methods for evaluating and treating cognitive impairment in elderly populations are inefficient and inconvenient, particularly for those with physical challenges or living in areas with healthcare shortages, as they require frequent hospital visits and lack personalized and effective training solutions.
Innovation Solution
A composite electronic system embedded with AI algorithms, comprising a hand-eye coordination training device, brain training application, and wearable electronic devices, that collects user data, performs cloud data analytics, and predicts cognitive impairment risk, recommending personalized cognitive training courses to enhance cognitive and physical abilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional cognitive function testing and treatment methods are used, then medical professionals can diagnose cognitive impairment, but patients must frequently visit hospitals which is inconvenient and inaccessible for physically challenged patients and those in health workforce shortage areas
Solution Approach 1:
The system enables patients to conduct cognitive function tests and receive personalized training independently at home through a digital product system. The automated AI algorithm generates test results and creates customized training programs without requiring professional intervention, allowing patients to serve themselves and eliminating the need for frequent hospital visits.
Solution Approach 2:
A digital product system comprising a tablet computer, interactive cognitive training apparatus, and wearable electronic device serves as an intermediary between patients and medical professionals. This intermediary delivers cognitive testing and training functions to patients' homes, bridging the gap between healthcare services and physically challenged or remote patients.
2Adaptability or versatility
If conventional cognitive training is provided, then patients can receive general rehabilitation exercises, but the training lacks personalization and effectiveness for individual cognitive needs
Solution Approach 1:
The system continuously monitors patient performance during cognitive tests and training exercises, feeding this data back to the AI algorithm. The algorithm analyzes the feedback to assess cognitive function accurately and adjusts the personalized training program accordingly, creating a closed-loop system that improves both assessment precision and training adaptability over time.
Solution Approach 2:
The system provides customized cognitive training that targets specific cognitive deficits identified in each patient's assessment results. Rather than applying uniform training to all patients, the AI algorithm generates locally optimized training programs tailored to individual cognitive needs, ensuring precise and effective intervention for each patient's unique condition.
3Reliability
If comprehensive cognitive testing and personalized training are provided, then treatment effectiveness improves, but the system complexity increases with multiple devices and AI algorithms
Solution Approach 1:
The digital product system integrates multiple functions into a unified platform: the tablet computer runs the cognitive test application and displays results, the wearable electronic device monitors physiological data, and the interactive cognitive training apparatus delivers personalized exercises. This multi-functional integration ensures reliable and comprehensive cognitive care while managing system complexity through coordinated design.
Data Source
AI summary
A digital product system for predicting risk of cognitive impairment and precisely cognitive training is disclosed. The digital product system is principally composed of a hand-eye coordination training device, a brain training application program, a wearable electronic device, and a cloud computing device, so as to include multiple functions of user data collecting, cloud data analytics, risk prediction of cognitive impairment, recommendation of individual training course. Therefore, the digital product system can be adopted for conducting a cognitive function test to a subject with high testing accuracy, and providing a precise cognitive training course to the subject who has completed the cognitive function test, so as to efficiently assist the subject in enhancement of cognitive ability. In addition, the digital product system can also be utilized for improving the symptoms in a patient with Parkinson's disease, mental illness, ADHD, or ASD.