Notification Filtering via Physiological Stress Detection

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Solution Overview

Problem

The increasing frequency and number of notifications from digital devices overwhelm users, causing cognitive stress and distraction, and existing predefined rule systems for managing notifications are complex and burdensome, discouraging their use.

Innovation Solution

A system that filters and prioritizes notifications based on physiological stress levels and contextual information, using sensors to collect data on user stress and applying machine-learning algorithms to determine when to deliver, delay, or withhold notifications, minimizing user interaction and maintaining notification relevance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If the system provides frequent notifications to keep users informed, then information availability is improved, but user cognitive load and stress increase

Engineering Contradiction:

Improveinformation availabilityVSAvoidcognitive load

Core Design Contradiction:

Loss of informationVSObject-affected harmful factors

Solution Approach 1:

The notification system dynamically adjusts its behavior based on real-time detection of user stress levels. When stress is detected, the system automatically reduces notification frequency or pauses non-critical notifications, creating a dynamic balance between information delivery and user well-being without requiring manual configuration

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback loops where physiological sensors continuously monitor user stress levels, and this feedback is used to modulate notification delivery in real-time. This closed-loop control ensures the system responds to user state changes and automatically adjusts to maintain optimal information flow

Inventive Principle:

Principle #23Feedback

2Ease of operation

If predefined rules are used to filter notifications, then notification management is simplified, but system complexity and maintenance burden increase

Engineering Contradiction:

Improvenotification managementVSAvoidrule configuration

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system performs self-configuration by automatically learning user patterns and stress responses over time. It eliminates the need for users to manually create or update filtering rules, as the system adapts to changing needs through machine learning, thereby simplifying operation while reducing configuration complexity

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary learning and adaptation during initial use and routine operation, building personalized notification strategies before users need to manually intervene. This preliminary action reduces the need for ongoing user configuration and maintenance

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11290553B2User-stress based notification system

Publication Date: 2022.03.29 INTEL CORP

AI summary

A system for filtering device information to be provided to a user by a digital device or system according to physiological information collected from the user. The physiological information may be used to determine the user's present cognitive stress, wherein the device information may be prioritized, withheld, delayed, or deleted if the present cognitive stress exceeds a predetermined threshold. The device information may be further evaluated with contextual information such as different aspects of the device information or non-physiological user information (e.g. location, time of the day). The system may manage device information with minimal or less user interaction than user defined rule systems.