Emotion Sensing AI via Eye Tracking Pupil Analysis
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Solution Overview
Problem
Current methods for determining emotional states in real-time, such as in virtual or augmented reality experiences, are prone to errors, invasive, and disrupt the user's experience due to the need for manual inputs or external sensors, making them costly and time-consuming.
Innovation Solution
An enhanced emotion sensing apparatus using eye tracking sensors to analyze pupil characteristics, such as position and size, to predict emotional states through artificial intelligence, allowing for dynamic adjustments to hardware devices without manual input, thereby providing a non-invasive and accurate emotional assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inputs or external sensors are used to determine emotional states, then emotional state determination can be achieved, but the user experience is disrupted and the system becomes invasive
Solution Approach 1:
The system uses existing eye tracking sensors that automatically capture pupil data without requiring user action. The emotional state determination is performed autonomously by the system through AI analysis of pupil characteristics, eliminating the need for manual inputs while maintaining continuous, non-invasive monitoring throughout the VR/AR experience.
2Measurement precision
If multiple external sensors are deployed to accurately sense emotions, then emotional state detection improves, but device complexity and cost increase
Solution Approach 1:
The patent repurposes existing eye tracking sensors, originally designed for gaze tracking, to also detect emotional states by analyzing pupil characteristics. This multi-functional use of a single sensor type eliminates the need for additional dedicated emotional sensing hardware, reducing device complexity while maintaining measurement precision through advanced AI analysis.
3Productivity
If continuous emotional monitoring is performed to provide real-time adjustments, then user experience optimization improves, but processing resources are consumed
Solution Approach 1:
The system performs emotional state determination continuously but only triggers hardware adjustments when actual emotional state changes are detected. This selective action approach maintains real-time monitoring capability for quick response when needed, while conserving computational resources during periods of stable emotional state by avoiding unnecessary adjustment operations.
Data Source
AI summary
Systems, apparatuses, and methods are directed toward determining emotional states of a subject. For example, the systems, apparatuses, and methods determine one or more previous characteristics of a pupil of an eye based on image data from eye tracking sensors, determine one or more current characteristics of the pupil based on image data from the eye tracking sensors, where the one or more current characteristics include one or more of a current position of the pupil or a current size of the pupil, track movements, based on image data from the eye tracking sensors, in a position of the pupil and changes in a size of the pupil over a time period, automatically predict an emotional state based on a comparison between the one or more previous characteristics and the one or more current characteristics, the tracked movements and the tracked changes in the size and adjust a parameter of one or more hardware devices based on the predicted emotional state.