Wearable Display Eye Response Control
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Solution Overview
Problem
Virtual reality devices cause eye fatigue and potential eye-related illnesses due to high visual stimulation, and existing AI systems lack effective methods to recognize and respond to user eye responses, especially for content featuring objects that trigger negative reactions.
Innovation Solution
An electronic device with a display, image capture device, and processor that learns user eye response characteristics to construct a user model, allowing for real-time processing of content features during reproduction, such as filtering or adjusting brightness and color to mitigate negative responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual reality content is displayed with high visual stimulation, then user immersion and engagement are improved, but eye fatigue and potential eye-related illnesses increase
Solution Approach 1:
The system captures real-time eye response data using an image capture device, processes this data to determine user reaction states, and dynamically adjusts content parameters based on this feedback loop. This allows the system to maintain high engagement while preventing eye fatigue by adapting to real-time physiological responses.
Solution Approach 2:
The system dynamically modifies content parameters such as brightness, color intensity, and contrast based on detected eye response characteristics. When eye fatigue is detected, the system adjusts these parameters to reduce visual stimulation, thereby maintaining engagement while preventing harmful effects.
2Device complexity
If AI systems use rule-based algorithms, then system complexity is reduced, but recognition accuracy and ability to understand user preference deteriorate
Solution Approach 1:
The system employs machine learning models that autonomously learn from eye response data without requiring explicit rule programming. The AI model self-improves its recognition accuracy by continuously processing and learning from captured eye movement patterns, eliminating the need for complex manual rule configuration while achieving high precision.
3Device complexity
If content is displayed without processing based on user response, then device complexity is reduced, but user comfort and experience quality deteriorate
Solution Approach 1:
The system performs preliminary analysis of eye response characteristics during content playback to predict potential discomfort. Based on this preliminary assessment, it proactively adjusts content parameters before significant eye fatigue occurs, thereby maintaining user comfort without requiring complex real-time processing during critical moments.
Data Source
AI summary
An example method of controlling an electronic device worn by a user includes constructing a user model by training a content feature according to response characteristics of an eye of a user who wears the electronic device, and in response to a content feature stored in the user model being detected from reproduced content during content reproduction, processing the reproduced content based on response characteristics of the eye of the user corresponding to the detected content feature.