Information Processing System for Personalized Lifestyle Action Prioritization
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Solution Overview
Problem
There is a growing demand for clinical evidence to support the effectiveness of Digital Therapeutics (DTx) in improving lifestyle and reducing chronic diseases, but existing systems lack effective methods to personalize and enhance the impact of lifestyle improvement actions.
Innovation Solution
An information processing system that uses at least one processor to analyze a target user's lifestyle data and present high-priority action categories, along with specific actions for the user to practice, thereby enhancing the effectiveness of lifestyle improvement actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If generic lifestyle improvement recommendations are provided to all users, then the system complexity is low, but the effectiveness and personalization of lifestyle improvement actions is poor
Solution Approach 1:
The patent segments lifestyle improvement recommendations into specific action categories (e.g., diet, exercise, sleep) and further divides them into prioritized action items within each category. This segmentation allows the system to provide personalized recommendations without requiring complete redesign of the entire recommendation engine, thus improving effectiveness while managing complexity.
Solution Approach 2:
The system performs preliminary analysis of user lifestyle data before generating recommendations. It pre-processes user data to identify action categories and prioritizes actions within those categories in advance. This preliminary action enables the system to deliver personalized recommendations efficiently without complex real-time processing during user interactions.
2Measurement precision
If comprehensive lifestyle data is collected and analyzed, then the personalization accuracy is improved, but the data processing time and computational resources increase
Solution Approach 1:
The patent extracts only the necessary lifestyle data elements required for generating personalized recommendations, rather than processing all available user data. It identifies and extracts key action categories and relevant lifestyle factors, reducing computational overhead while maintaining personalization accuracy.
Solution Approach 2:
The system performs partial analysis by focusing on specific action categories and prioritizing a limited number of key actions within each category. Rather than comprehensively analyzing all possible lifestyle factors, it concentrates computational resources on the most impactful areas, achieving good personalization with reduced processing time.
3Reliability
If multiple action categories and specific actions are presented to users, then the effectiveness of lifestyle improvement is enhanced, but the information overload and user decision difficulty increase
Solution Approach 1:
The patent applies local quality by providing different levels of detail and prioritization for different action categories based on user needs and preferences. Each action category receives customized presentation with prioritized actions, allowing users to focus on the most relevant recommendations without being overwhelmed by all possible actions simultaneously.
Solution Approach 2:
The system presents a partial view of available actions by prioritizing and displaying only the most important actions within each action category. Rather than showing all possible actions, it selects and presents a manageable subset, making user decision-making easier while maintaining effectiveness through strategic selection of high-impact actions.
Data Source
AI summary
A technology to support improvement in effectiveness of lifestyle improvement actions is provided. An information processing system includes at least one processor, wherein the at least one processor presents at least one high-priority action category based on information about lifestyle of a target user, and presents the target user with at least one action to be practiced by the target user in relation to the presented action category.