Eye-Tracking Mental Condition Analysis Without Verbal Interaction
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Solution Overview
Problem
Existing technologies struggle to correlate non-verbal changes in human subjects with mental and physiological conditions, and effectively analyze these changes for therapeutic or educational purposes.
Innovation Solution
A computerized platform that generates challenges for human subjects, detects non-verbal responses through eye tracking, and classifies mental conditions without verbal interaction, using a computer processor to select specific locations based on subject data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional verbal interaction methods are used to diagnose mental conditions, then the depth of information gathering may be improved, but the level of cooperation required from subjects increases and the diagnosis process becomes less efficient
Solution Approach 1:
The patent replaces verbal interaction (mechanical communication system) with eye tracking technology (optical detection system). The eye tracker captures subtle eye movements and pupil responses that reveal mental states without requiring verbal communication, thus reducing the cooperation burden while maintaining diagnostic information quality.
Solution Approach 2:
The patent introduces eye tracking technology as an intermediary between the subject and the diagnostic process. Instead of direct verbal interaction, the system uses eye movement patterns as an intermediate indicator of mental state, enabling indirect but accurate assessment of conditions like stress and anxiety.
2Loss of information
If verbal interaction is required for mental condition assessment, then detailed information can be obtained, but the intrusiveness of the process increases
Solution Approach 1:
The patent substitutes verbal questioning (intrusive mechanical interaction) with passive optical eye tracking. The system observes natural eye movements and pupil responses without requiring the subject to speak or engage actively, thereby reducing intrusiveness while capturing detailed mental state information.
Solution Approach 2:
The subject's own physiological responses (eye movements, pupil dilation) serve as the diagnostic data source without requiring active participation. The subject essentially diagnoses themselves through their involuntary physiological reactions to stimuli, reducing the need for cooperative verbal interaction.
3Measurement precision
If complex analysis methods are used to interpret non-verbal changes, then diagnostic accuracy may improve, but the system complexity increases
Solution Approach 1:
The patent replaces complex human analysis of non-verbal cues with automated computer vision algorithms. The system uses machine learning models to interpret eye tracking data, automatically detecting patterns associated with specific mental conditions without requiring complex manual analysis procedures.
Data Source
AI summary
A method and a system for analyzing and treating mental conditions of a human subject based on eye tracking are provided herein. The method may include: receiving human subject data associated with a mental or a physical condition related to a human subject; and instructing the human subject, via a user interface, to look at a specific location, while thinking about something associated with the mental or physical condition, wherein the specific location is automatically selected by a computer processor, based on said human subject data.