Biometric and Application Data Correlation for Health Insights
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing health and wellness applications fail to provide the most effective insights for improving user health and wellness, as they do not adequately utilize both biometric and application data to offer personalized recommendations.
Innovation Solution
A system comprising wearable devices and user devices that collect biometric data and application data to provide insights and recommendations, using machine learning classifiers and circadian rhythm adjustment models to determine content that regulates biometric data, such as scheduling events to improve sleep scores or readiness scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing health and wellness applications only use basic biometric data, then the system complexity remains low, but the effectiveness of health insights and recommendations is insufficient
Solution Approach 1:
The patent combines multiple data sources including biometric data, application data, and calendar data into a unified analysis system. This merging of diverse data types enables comprehensive health insights by correlating physiological measurements with user activities and scheduled events, thereby improving insight effectiveness while managing system complexity through integrated processing.
Solution Approach 2:
The system is designed to handle multiple types of data (biometric, application, calendar) and provide various health-related insights (sleep quality, readiness, stress management) through a single platform. This multi-functional approach allows the system to serve diverse health monitoring needs without requiring separate specialized systems, improving overall effectiveness while maintaining reasonable complexity.
2Adaptability or versatility
If the system collects and analyzes both biometric data and application data, then personalized health insights are improved, but data processing complexity increases
Solution Approach 1:
The system performs preliminary processing and organization of biometric and application data before generating health insights. By pre-processing data streams, categorizing information, and establishing baseline metrics in advance, the system reduces the complexity of real-time analysis while enabling highly personalized insights through pre-established data relationships and patterns.
Solution Approach 2:
The patent introduces intermediate processing layers that mediate between raw data collection and final insight generation. These intermediary components include data normalization modules, correlation analysis engines, and pattern recognition systems that translate complex multi-source data into actionable health recommendations, thereby managing processing complexity while maintaining personalization capabilities.
Data Source
AI summary
Methods, systems, and devices for content delivery are described. A device may receive biometric data associated with a user from a wearable device, and receive application data associated with the user from the device. The application data may be indicative of a previous activity in which the user engaged or an upcoming activity in which the user is to engage. The device may determine content for recommending to the user based on correlating the received biometric data and the received application data. The content may correspond to a respective effectiveness for regulating the received biometric data. In some examples, the content may facilitate improvements to the user’s health and wellness. The device may cause a graphical user interface (GUI) of the device running an application to display the content for recommending to the user based on correlating the received biometric data and the received application data.