AI Well-Being Monitoring With Pattern-Based Content Delivery
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Solution Overview
Problem
There is a growing need for accessible and efficient means to monitor and address the interlinked states of physical, mental, and financial well-being, as existing systems are often siloed, labor-intensive, and lack real-time, personalized support for managing stress and preventing negative health outcomes.
Innovation Solution
A system and method utilizing artificial intelligence to analyze user data from various sources, identify patterns, and deliver personalized digital content to users, including video, audio, and written guidance, to promote positive well-being through a mobile app.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If highly qualified personnel are used to analyze user data for well-being assessment, then measurement precision is improved, but device complexity and labor cost increase
Solution Approach 1:
The patent replaces manual analysis by highly qualified personnel with an automated AI system comprising machine learning models and algorithms that process user data from multiple sources (wearable devices, mobile apps, surveys) to assess physical, mental, and financial well-being, thereby maintaining measurement precision while eliminating the need for human analysts
Solution Approach 2:
The system enables self-service well-being assessment where users automatically provide data through integrated devices and apps, and the AI system autonomously processes this data to generate personalized insights and recommendations without requiring human intervention for data collection or analysis
2Measurement precision
If comprehensive user data is collected from multiple sources, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system continuously collects and pre-processes user data in the background from wearable devices, mobile applications, and surveys before formal assessment is needed, maintaining updated profiles of physical, mental, and financial well-being indicators so that real-time or near-real-time assessment can be performed without time-consuming data gathering
Solution Approach 2:
The system implements continuous monitoring and processing of user data streams from multiple sources simultaneously, with parallel data collection, validation, and analysis operations that maintain constant well-being assessment capability without interruption or time loss
3Adaptability or versatility
If personalized digital content is delivered to users, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system delivers personalized digital content by tailoring recommendations, insights, and interventions to each user's specific well-being profile, needs, and preferences across different domains (physical, mental, financial health), providing locally optimized content for each user rather than generic information
Solution Approach 2:
The system segments users into different categories based on their well-being profiles and divides content delivery into specialized modules for physical health, mental health, and financial well-being, allowing personalized content to be delivered through separate, manageable components rather than a monolithic system
Data Source
AI summary
A system for monitoring data representative of a user's general wellbeing and for delivering digital content to the user, the system comprising a pre-defined module comprising a plurality of reference patterns mapped to digital content for delivery to the user, the system further comprising at least a processing means, wherein the processing means is configured to: identify user activity and select a user based on the identified user activity; for the selected user, interrogate user data representative of the user's general wellbeing and identify a pattern in said user data; and compare the identified pattern to the reference patterns in the pre-defined module to identify digital content mapped with the identified pattern.