Coordinating Wearable Devices via Biometric Pattern Analysis
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Solution Overview
Problem
Existing wearable electronics systems lack effective coordination between multiple devices, limiting their ability to predict and respond to recurring events based on shared biometric and social media data patterns.
Innovation Solution
A system that integrates biometric data from wearable devices with social media data to identify patterns, using machine learning algorithms to generate trigger thresholds for predicting recurring events and initiating coordinated communications or actions between users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple wearable devices are used to collect biometric data, then the quantity and variety of data increases, but the coordination and integration between devices is lacking
Solution Approach 1:
The patent merges data from multiple wearable devices by integrating biometric data streams from different devices into a unified analysis system. The system combines heart rate data, activity data, and other biometric measurements from multiple devices to identify coordinated patterns, effectively merging the functionality of separate devices into a coordinated multi-device system.
2Measurement precision
If biometric data from multiple devices is integrated, then pattern recognition accuracy improves, but system complexity increases
Solution Approach 1:
The patent introduces a server or cloud-based platform as an intermediary that receives, processes, and analyzes biometric data from multiple wearable devices. This intermediary handles the complex tasks of data integration, pattern recognition, and coordinate identification, thereby improving measurement precision while isolating the complexity from the user-facing wearable devices themselves.
3Measurement precision
If the system analyzes history data to identify patterns, then prediction accuracy for recurring events improves, but data processing time increases
Solution Approach 1:
The patent performs preliminary analysis of historical biometric data to identify recurring patterns and events in advance. By analyzing history data beforehand to establish baseline patterns of coordinated events (such as recurring health events or activity patterns), the system prepares prediction models that can quickly recognize and respond to similar future events without requiring extensive real-time processing.
4Ease of operation
If the system initiates coordinated communications between users, then user experience improves, but communication coordination complexity increases
Solution Approach 1:
The patent uses a centralized server or platform as an intermediary to manage coordinated communications between users. The server handles the complex logic of determining when coordinated notifications should be sent, what messages to deliver, and how to synchronize communications across multiple devices and users, thereby improving user experience while containing communication coordination complexity within the server infrastructure.
Data Source
AI summary
In various example embodiments, devices including a wearable device may be associated to share information and coordinate data between the devices as part of a coordination between relationship wearables. For example, a first wearable device and a second device, each associated with different users, may provide data to a history analysis module. The history analysis module may analyze this data for coordinated relationship patters made up of repeated events. Coordinated relationship data may be generated by this analysis, and then used by a current data analysis module to analyze an incoming stream of current data from at least one of the devices. When a repeated status value is identified within the current data stream, a coordination communication may be initiated.