Mental State Data Tagging for Multi-Source Analysis

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Solution Overview

Problem

Current methods for evaluating human-computer interaction and user mental states are unreliable, subjective, and impractical, as they rely on self-reporting, surveys, or third-party observations, which are not scalable or accurate in capturing user emotions and preferences during interactions with computers or media consumption.

Innovation Solution

A computer-implemented method for mental state analysis that captures and tags mental state data from multiple sources, including facial expressions, biosensors, and contextual information, and sends it to a web service for analysis to generate insights on user emotions and preferences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If self-reporting surveys are used to evaluate user mental states, then user feedback can be collected, but the reliability and accuracy of the data deteriorates due to subjectivity and low participation rates

Engineering Contradiction:

Improveease of data collectionVSAvoidreliability of mental state data

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent replaces the mechanical system of self-reporting surveys with an automated optical detection system using cameras and image processing algorithms. The system automatically captures facial expressions and analyzes them through computer vision techniques, eliminating the need for manual survey completion while providing objective, reliable mental state data without user subjectivity or participation bias

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the user's own facial expressions to automatically generate the evaluation data without requiring active participation. The camera captures and the system autonomously processes the facial imagery to derive mental state information, making the data collection process passive for the user while maintaining high reliability

Inventive Principle:

Principle #25Self-service

2Measurement precision

If third-party observers are used to evaluate user mental states, then accurate observations can be obtained, but the complexity and cost of the system increases due to need for trained observers

Engineering Contradiction:

Improveaccuracy of mental state observationVSAvoidcomplexity of observation system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent substitutes the mechanical system of trained human observers with an automated computer-based image processing system. The system uses algorithms to detect and analyze facial expressions, replacing the need for trained observers while maintaining measurement precision through automated computer vision techniques that consistently evaluate facial imagery without human subjectivity or fatigue

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system creates a digital copy of the observation process by capturing facial expressions through cameras and processing them through software algorithms. This digital copy replicates and enhances the observation capability, allowing multiple analyses simultaneously without the complexity of coordinating multiple trained human observers

Inventive Principle:

Principle #26Copying

3Loss of information

If multiple data sources are collected for mental state analysis, then the comprehensiveness of the analysis improves, but the complexity of data processing and integration increases

Engineering Contradiction:

Improvecompleteness of mental state informationVSAvoidcomplexity of multi-source data processing

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent merges multiple data sources by integrating facial expression data from cameras with other potential data streams into a unified analysis framework. The system combines these diverse inputs and processes them through a centralized algorithm that synthesizes the information to produce comprehensive mental state analysis, reducing the complexity that would arise from handling separate data streams independently

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS9646046B2Mental state data tagging for data collected from multiple sources

Publication Date: 2017.05.09 AFFECTIVA

AI summary

Mental state data useful for determining mental state information on an individual, such as video of an individual's face, is captured. Additional data that is helpful in determining the mental state information, such as contextual information, is also determined. The data and additional data allows interpretation of individual mental state information. The additional data is tagged to the mental state data and at least some of the mental state data, along with the tagged data, can be sent to a web service where it is used to produce further mental state information.