Predictive Tracking Device for Mood and Health Forecasting
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Solution Overview
Problem
Current methods for tracking user mood and health symptoms lack the ability to predict future states based on objective and subjective data, failing to provide proactive management and remediation recommendations effectively.
Innovation Solution
A predictive tracking method and apparatus that collects user and environmental state data, associates them based on temporal and spatial correlations, and uses this information to forecast future user states, providing alerts and remediation recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If predictive tracking is implemented to forecast future user states, then proactive management capability is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing training data in advance to build predictive models. Environmental data and user state data are gathered beforehand, and correlation analyses are conducted proactively to forecast future states before they occur, enabling early intervention and management.
Solution Approach 2:
The patent introduces an intermediary predictive modeling layer that mediates between raw data collection and user state forecasting. This intermediary component processes environmental and user state data through correlation analysis and machine learning models, transforming complex multi-source data into actionable predictions without requiring direct complex interactions between all data elements.
2Measurement precision
If multiple data sources are integrated for comprehensive tracking, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments data collection and processing into distinct modules: environmental data collection, user state data collection, data association/correlation, and predictive modeling. Each module handles specific data types and processing tasks independently, allowing comprehensive multi-source integration while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The patent implements a universal data association framework that can handle multiple data sources (environmental sensors, user inputs, health metrics) through a common correlation analysis mechanism. This multi-functional approach allows the same processing infrastructure to accommodate various data types and prediction scenarios, reducing overall system complexity.
Data Source
AI summary
A predictive tracking method and apparatus utilizing objective and subjective data in order to predict user states is provided herein. For example, some such embodiments may allow a user to track their mood or health symptoms in relation to retrieved data regarding their environmental in order to reveal patterns that can help forecast and proactively manage mood or health symptoms.