Wellness Recommendation System Using Multi-Source Data Integration
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Solution Overview
Problem
Existing technologies are fragmented and unintegrated, failing to provide unified, consistent, comprehensive, or real-time advice for managing wellness across psychological, physiological, and financial categories.
Innovation Solution
A method and system that receive user data from wearable devices, financial, and psychological sources, calculate current user scores, compare them to standards, and provide personalized recommended behaviors to improve wellness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple data sources (wearable devices, financial, psychological) are integrated to provide comprehensive wellness recommendations, then the comprehensiveness and personalization of advice is improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent merges multiple data sources including wearable device data, financial data, and psychological data into a unified wellness assessment system. This integration allows comprehensive evaluation across physical, financial, and psychological dimensions, resolving the contradiction by combining disparate systems into a cohesive platform that delivers holistic wellness recommendations.
Solution Approach 2:
The system is designed to handle multiple types of data (physiological, financial, psychological) and provide universal wellness recommendations across different user needs and contexts. This multi-functional approach enables the system to adapt to various wellness domains while maintaining a unified architecture, addressing both comprehensiveness and complexity concerns.
2Loss of time
If real-time data processing and personalized recommendations are provided across multiple wellness categories, then the relevance and timeliness of advice is improved, but the computational resources and processing time required increase
Solution Approach 1:
The system performs preliminary data processing and wellness assessment calculations in advance, establishing baseline scores and comparison standards for multiple wellness categories before real-time recommendations are needed. This pre-computation reduces the computational burden during real-time operations, enabling timely recommendations while managing energy consumption.
Solution Approach 2:
The system implements continuous feedback loops where user responses to recommendations and changes in wellness metrics are processed to dynamically adjust future recommendations. This feedback mechanism optimizes computational resources by focusing processing on relevant, changing parameters rather than continuously analyzing all data points, thereby reducing energy consumption while maintaining timeliness.
3Measurement precision
If detailed user data collection and analysis are performed across physical, financial, and psychological domains, then the accuracy of wellness assessment is improved, but the privacy concerns and data security requirements increase
Solution Approach 1:
The system introduces intermediary processing layers that aggregate and anonymize user data before storage and analysis. Personal identifiers are separated from wellness metrics, and data is processed through intermediate representations that maintain assessment accuracy while reducing direct exposure of sensitive personal information, thereby addressing privacy concerns without sacrificing precision.
Data Source
AI summary
In one embodiment, the present disclosure is directed to a method for providing a recommended wellness behavior. User data is received for different wellness components, the user data including data related to physical health, finances, and psychology. A user's wellness is assessed by, for each wellness component, determining a deviation between a comparison score and a relevant standard. A recommended behavior is determined based on the determined deviation. An indicator of the recommended behavior is then output to the user for the user to perform.