Wearable Physiological Insight System Using Taggable Event Patterns

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Solution Overview

Problem

Existing wearable devices fail to effectively provide insights that are most effective in causing specific physiological responses for individual users, as they do not adequately link taggable events with physiological responses and rely on manual user input for tagging.

Innovation Solution

A system that includes a wearable device and a user device, which collects physiological data and uses a set of tags relevant to taggable events to provide insights. The system prompts users for feedback on identified taggable events, increasing the number of tags and events, and determines patterns between physiological thresholds and taggable events to improve user insights.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If manual user input for tagging events is used, then device complexity is reduced, but the quantity of taggable events and insights is insufficient

Engineering Contradiction:

Improvenumber of taggable eventsVSAvoidmanual user input requirement

Core Design Contradiction:

Quantity of substanceVSEase of operation

Solution Approach 1:

The system automatically identifies taggable events by analyzing physiological data patterns without requiring manual user input. The device detects events such as sleep periods, exercise sessions, and stress episodes autonomously by monitoring physiological parameters and comparing them against predefined thresholds and patterns.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The manual tagging mechanism is replaced with an automated detection system that uses physiological data analysis. Instead of users manually entering tags, the system substitutes this mechanical input process with automated pattern recognition algorithms that analyze physiological signals to identify and tag events.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If post-activity analysis is used, then device complexity is reduced, but the ability to provide timely and personalized insights is limited

Engineering Contradiction:

Improveinsight generation speedVSAvoidpattern recognition system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary analysis by continuously monitoring physiological data during activities and pre-identifying potential events as they occur. Rather than waiting for post-activity analysis, the system proactively detects events in real-time and prepares insights immediately, enabling timely feedback during or right after activities.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements a feedback loop where physiological data is continuously analyzed, insights are generated and presented to users, and user responses are incorporated to refine future insights. This creates a dynamic system that learns from user interactions and continuously improves personalized insight delivery.

Inventive Principle:

Principle #23Feedback

3Reliability

If conventional insight techniques are used, then ease of operation is maintained, but the effectiveness in causing specific physiological responses is insufficient

Engineering Contradiction:

Improveeffectiveness of physiological responseVSAvoidpattern analysis system

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system provides localized and personalized insights tailored to each user's specific physiological patterns, behaviors, and goals. Rather than generic insights, the system analyzes individual user data to deliver customized recommendations that address specific physiological responses and personal health objectives.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The insight generation system is dynamic and adapts to changing user conditions, behaviors, and physiological states. The system continuously updates its analysis based on new data, evolving user patterns, and changing goals, making the insight delivery flexible and responsive rather than static.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12288473B2Techniques for providing insights according to tags and physiological data

Publication Date: 2025.04.29 OURA HEALTH OY

AI summary

Methods, systems, and devices for physiological pattern recognition are described. A device may receive physiological data associated with a user from a wearable device. The device may determine that at least one physiological parameter associated with the received physiological data satisfies a physiological threshold associated with a pattern between the physiological threshold and a taggable event or a set of taggable events defined within an application associated with the wearable device. The device may then identify, based on the pattern, the taggable event or the set of taggable events indicating an activity the user engaged in that contributed to the at least one physiological parameter satisfying the physiological threshold, and cause a graphical user interface (GUI) of the device running the application to prompt the user to provide feedback associated with the identified taggable event or the identified set of taggable events.