Eye Gaze Adaptive Display Illumination for Power Efficiency
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Solution Overview
Problem
Display panels that adjust brightness levels dynamically based on user activity and eye gaze patterns are needed to reduce power consumption and enhance user productivity, as existing technologies often result in unintended illumination patterns and lack adaptability to changing user activities.
Innovation Solution
An electronic device that monitors user eye gaze patterns using machine learning techniques and adjusts display panel illumination accordingly, storing patterns and conditions to selectively illuminate different areas based on identified user behavior and environmental factors during a training period.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If display panel illuminates all areas uniformly at high brightness, then user can see content clearly across the entire screen, but power consumption increases excessively
Solution Approach 1:
The display panel applies different brightness levels to different regions based on where the user is actually looking. The central foveal region receives higher brightness while peripheral regions receive lower brightness, optimizing power consumption while maintaining visual comfort and readability.
Solution Approach 2:
The illumination pattern dynamically adjusts based on real-time eye tracking data. As the user moves their gaze across the screen, the bright region follows the foveal position, ensuring optimal brightness is always provided where needed while minimizing overall power consumption.
2Adaptability or versatility
If display panel uses static illumination patterns, then device complexity is reduced, but adaptability to changing user activities decreases
Solution Approach 1:
The system automatically adapts illumination patterns by monitoring eye gaze patterns and user interactions without requiring manual configuration. Machine learning algorithms process usage data to identify patterns and automatically adjust display characteristics, eliminating the need for complex manual setup while providing high adaptability.
Solution Approach 2:
The system continuously monitors user eye gaze and interaction patterns, using this feedback to dynamically adjust illumination patterns. The eye tracking camera and sensors provide real-time feedback about user attention, which the system uses to optimize display brightness distribution automatically.
3Adaptability or versatility
If display panel monitors and analyzes eye gaze patterns continuously, then adaptability to user activity improves, but use of energy increases
Solution Approach 1:
The eye tracking and monitoring operations are performed periodically rather than continuously, reducing energy consumption while still capturing sufficient data to identify usage patterns. The system samples eye position at intervals and processes data batch-wise, balancing adaptability with power efficiency.
4Productivity
If display panel applies complex illumination patterns, then user productivity is enhanced through better visibility, but device complexity increases
Solution Approach 1:
The display panel is divided into multiple regions with different brightness levels, with the brightest region centered on the user's foveal gaze position. This segmentation allows complex illumination patterns to be implemented using relatively simple per-region brightness control, enhancing productivity without requiring overly complex system architecture.
Data Source
AI summary
In some examples, a computer-readable medium storing executable code which, when executed by a processor of an electronic device, causes the processor to store a relationship between a user eye gaze pattern and first conditions of the electronic device, identify second conditions of the electronic device, determine whether the second conditions match the first conditions, and responsive to the second conditions matching the first conditions, selectively operate a display panel of the electronic device with differing display characteristics based on the user eye gaze pattern.