Cognitive Load Scoring for Visual Stimuli

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Solution Overview

Problem

Current digital design systems lack the ability to quantitatively measure and optimize the cognitive load of visual stimuli, leading to suboptimal user experiences and inefficiencies in design iteration, as they cannot accurately predict how effectively information is transmitted to viewers across different devices and formats.

Innovation Solution

The development of an information density toolkit system that uses an information density matrix to characterize feature points in a visual stimulus, identify clusters, and determine a cognitive load score, allowing for the modification of design to adjust cognitive load, incorporating tools for cognitive load scoring, behavioral intent estimation, color-emotion analysis, and visual attention likelihood estimation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If information density is increased to communicate more content, then information transmission capability is improved, but cognitive load increases making it harder for users to process

Engineering Contradiction:

Improveinformation transmission capabilityVSAvoidcognitive load

Core Design Contradiction:

Loss of informationVSObject-affected harmful factors

Solution Approach 1:

The patent segments visual information into discrete feature points and clusters, allowing the system to analyze and optimize information density at a granular level. By identifying clusters of feature points rather than treating the entire visual stimulus as a single unit, the system can selectively adjust information density in different regions to balance information transmission with cognitive load management.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the parameter of information density by analyzing the spatial distribution and clustering of feature points. The cognitive load score is calculated based on the number, density, and spatial arrangement of feature point clusters, allowing quantitative measurement and optimization of the balance between information content and cognitive processing requirements.

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If design is customized for individual viewers and devices, then user experience is improved, but design complexity increases

Engineering Contradiction:

Improvedesign adaptabilityVSAvoiddesign complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent uses parameter changes by calculating cognitive load scores based on quantifiable features such as the number of feature point clusters, their spatial distribution, and density. These parameters provide an objective basis for automatically adapting design to different viewers and devices, reducing the need for manual customization while maintaining high adaptability.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements feedback by using cognitive load scoring to evaluate design effectiveness and guide iterative optimization. The system provides quantitative feedback on how design modifications affect cognitive load, enabling data-driven decisions for adapting designs across different contexts without requiring complex manual adjustments.

Inventive Principle:

Principle #23Feedback

3Productivity

If cognitive load scoring is implemented to optimize design, then user experience and conversion rates are improved, but measurement and analysis complexity increases

Engineering Contradiction:

Improvedesign effectivenessVSAvoidcognitive load measurement

Core Design Contradiction:

ProductivityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent replaces subjective human evaluation of cognitive load with an automated computational system. Instead of relying on human experts to assess cognitive demand, the system uses algorithmic analysis of feature point clusters and spatial distribution to objectively calculate cognitive load scores, making measurement more systematic and scalable.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates a simplified representation or copy of the visual stimulus by extracting feature points and their spatial relationships. This abstracted model captures the essential cognitive processing requirements without requiring analysis of the complete original design, reducing measurement complexity while maintaining accuracy.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS12118763B2Cognitive load scoring of a visual stimulus

Publication Date: 2024.10.15 DELL PROD LP

AI summary

An apparatus comprises at least one processing device comprising a processor coupled to a memory. The at least one processing device is configured to obtain an information density matrix for an input visual stimulus, the information density matrix characterizing information density of feature points in the input visual stimulus, and to identify one or more clusters of feature points in the input visual stimulus by performing spatial clustering of the feature points utilizing the information density matrix. The at least one processing device is also configured to determine a cognitive load score for the input visual stimulus based at least in part on the identified one or more clusters of feature points, the cognitive load score characterizing cognitive energy required to mentally process the input visual stimulus. The at least one processing device is further configured to modify a design of the input visual stimulus to adjust the cognitive load score of the input visual stimulus.