EEG Interface System Eye Movement Timing Adjustment
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Solution Overview
Problem
Existing electroencephalogram interface systems are inefficient in allowing users to select options from a large number of choices without causing inconvenience or frustration, as they require waiting for options to be highlighted and maintaining gaze during unwanted highlights, leading to long selection times and unnecessary distraction.
Innovation Solution
An electroencephalogram interface system that measures eye movements to determine when to begin highlighting and adjust the timing and interval of highlighting based on user gaze, using an electroencephalogram measurement section to identify event-related potentials and an output section to present options on a screen, thereby allowing users to efficiently select desired options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If options are individually highlighted one by one, then the user can clearly see each option, but the time required for selection becomes excessively long
Solution Approach 1:
The patent segments the highlighting process by dividing options into groups and highlighting only selected groups simultaneously based on eye movement data, rather than highlighting each option individually. This segmentation reduces the total number of highlighting operations while maintaining clear visibility of relevant options.
Solution Approach 2:
The system performs preliminary action by measuring eye movements and predicting the user's target option before the actual selection is made. By analyzing gaze patterns and fixation points in advance, the system can pre-highlight the most likely target options, reducing the time needed for final selection.
2Productivity
If all options are highlighted simultaneously, then the selection process is faster, but the user becomes distracted and unable to focus on the desired option
Solution Approach 1:
The patent applies local quality by highlighting only specific regions or groups of options based on eye movement analysis, rather than uniformly highlighting all options. This creates different visual qualities in different parts of the interface, with high emphasis on predicted target areas and low or no emphasis on other areas, thereby reducing distraction while maintaining selection speed.
Solution Approach 2:
The system uses feedback from eye movement measurement to dynamically adjust which options are highlighted. By continuously monitoring gaze patterns and using this feedback to control the highlighting state, the system adapts to user intent in real-time, presenting only relevant options for selection and avoiding unnecessary visual distractions.
3Device complexity
If the highlighting timing is fixed and predetermined, then the system operation is simple, but the user must wait unnecessarily and experience frustration
Solution Approach 1:
The patent implements dynamics by making the highlighting timing adaptive rather than fixed. The system dynamically adjusts when to highlight options based on real-time eye movement data, allowing the highlighting to occur at the optimal moment when the user is most likely to be ready for selection. This dynamic approach significantly improves user convenience while adding manageable complexity.
Solution Approach 2:
The system practices self-service by automatically determining the optimal highlighting timing through eye movement analysis without requiring user input or manual adjustment. The system serves itself by using its own measurement capabilities to control its operation, adapting to each user's natural viewing patterns and eliminating unnecessary waiting times.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the time required for option selection and minimizes unnecessary highlighting, enhancing user experience by allowing clear and undecided users to choose options quickly and smoothly without feeling frustrated.
Implementation Method 1
an electroencephalogram measurement section for measuring an electroencephalogram signal
Implementation Method 2
an eye movement measurement section for measuring an eye movement
Data Source
AI summary
An electroencephalogram interface system includes: sections for measuring an electroencephalogram and an eye movement; an output section for presenting on a screen an option related to a device operation; a highlight determination section for, if a predetermined time has elapsed since a rotational angular velocity of the eye movement becomes equal to or less than a threshold value, identifying a region of the screen in which the user is fixing one's gaze based on the eye movement, and determining an option to be highlighted; an interface section for highlighting the determined option, and determining an operation of the device based on an event-related potential in the signal based on the timing of highlighting the option; and a timing adjustment section for adjusting a timing of beginning highlighting based on the eye movement after a process of displaying the option on the screen is begun and until the option is displayed on the screen.