Cognitive State Estimation via Behavior and Context Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current behaviomedics technologies face challenges in accurately estimating cognitive states due to the complexity of human behavior and the limitations of remote assessments, which can miss nuances present in face-to-face interactions, and there is a need for improved methods to automate the analysis of emotional and internal cognitive states.
Innovation Solution
A computer-implemented cognitive state estimation method that receives a recording of a user and context primitives, extracts behavior and context descriptors, produces behavior and context maps through Fourier transforms, and estimates cognitive states using a combination of convolutional neural networks and neural processes to analyze behavior primitives and context information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If remote assessment methods are used to estimate cognitive states, then automation and accessibility are improved, but measurement precision deteriorates due to missed nuances
Solution Approach 1:
The patent segments the assessment into multiple context primitives (time, location, weather, task features) and behavior primitives (facial actions, gestures, voice characteristics). This segmentation allows comprehensive analysis of nuanced behaviors that can be captured remotely, resolving the contradiction between automation and measurement precision by breaking down complex behavior into analyzable components.
Solution Approach 2:
The patent introduces a new dimension by integrating multiple types of data (context primitives and behavior primitives) into a unified assessment framework. By combining temporal, environmental, and behavioral dimensions, the system achieves both automation and high measurement precision through multi-dimensional data fusion.
2Measurement precision
If multiple data sources are integrated for comprehensive assessment, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments data processing into distinct modules: context primitive extraction, behavior primitive extraction, behavior map generation, context map generation, and cognitive state estimation. This modular segmentation reduces overall system complexity while maintaining comprehensive data integration for high measurement precision.
Solution Approach 2:
The patent introduces behavior maps and context maps as intermediary representations that bridge raw data and final cognitive state estimates. These intermediary structures simplify the processing pipeline by organizing complex data relationships before final analysis, reducing computational complexity while preserving measurement precision.
Data Source
AI summary
A computer implemented cognitive state estimation method (10) comprising: receiving a recording of a user and at least one context primitive (11), each context primitive comprising a time series of context descriptors; extracting at least one behaviour primitive from the recording (12), each behaviour primitive comprising a time series of behaviour descriptors; producing a behaviour map from the at least one behaviour primitive (13); producing a context map from the at least one context primitive (14); and estimating a cognitive state of the user using data derived from the behaviour map and the context map (15).