Dynamic Icon Selection via Eye Movement Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Man-Machine Interface (MMI) technologies based on eye contact are not intuitive and efficient, as they require complex eye movement tracking and calibration, which is not effectively addressed by existing systems.
Innovation Solution
A system and method that uses dynamic icons with unique visual characteristics, where eye responses are analyzed to identify the selected icon, allowing for hands-free interaction without the need for precise eye location tracking, using sensors and controllers to interface with machines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex eye movement tracking and calibration are used, then eye contact-based MMI can be achieved, but the system complexity and calibration requirements increase
Solution Approach 1:
The patent extracts only the essential eye movement characteristics (fixation points and saccade patterns) needed for icon selection, discarding the need for comprehensive eye tracking calibration. This selective extraction simplifies the system while maintaining functional reliability for hands-free interface interaction.
Solution Approach 2:
The system uses the user's natural eye movement patterns without requiring active calibration or adjustment. The eye tracker passively captures fixation points and saccade characteristics as they occur naturally during icon viewing, eliminating the need for calibration procedures while maintaining accurate selection capability.
2Measurement precision
If precise eye location tracking is used, then accurate icon selection can be achieved, but the system requires more complex calibration and tracking infrastructure
Solution Approach 1:
The patent segments the eye movement signal into distinct components: fixation points (indicating icon viewing) and saccade patterns (indicating selection intent). By analyzing these segmented components rather than continuous eye position data, the system achieves accurate icon selection without requiring precise continuous eye location tracking or complex calibration.
Solution Approach 2:
The system uses partial eye movement information (fixation duration and saccade direction) rather than complete eye position data. This partial information approach provides sufficient precision for icon selection while dramatically reducing the calibration and tracking infrastructure requirements.
3Ease of operation
If traditional eye tracking methods are used, then eye movement data can be captured, but the system lacks intuitiveness and efficiency for hands-free interaction
Solution Approach 1:
The patent applies different analysis methods to different phases of eye movement: fixation duration analysis during icon viewing and saccade pattern analysis during selection transitions. This localized quality approach extracts meaningful interaction intent from specific eye movement phases, improving hands-free interaction efficiency while utilizing eye movement characteristics effectively.
Solution Approach 2:
The system provides feedback by analyzing the relationship between fixation points (where the user looks) and saccade patterns (how the user moves between icons). This feedback mechanism enables intuitive hands-free selection by detecting the user's natural eye movement patterns without requiring explicit commands, thereby improving interaction efficiency while preserving eye movement information.
Data Source
AI summary
There is provided herein a system for identifying a selected icon, the system comprising at least one controller configured to obtain from a sensor a signal indicative of an eye-response of a user, said eye-response is responsive to at least one dynamic property of a dynamic icon selected by the user by watching said selected dynamic icon, analyze said eye-response of said user, identify said selected dynamic icon based on said analysis, and produce a signal indicative of said selected dynamic icon.