Gaze-Based Prediction Device for Intuitive Pen Interaction
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Solution Overview
Problem
Current pen-based interaction systems rely heavily on multi-finger gestures, context/pop-up menus, and external buttons, which disrupt seamless interaction and require significant user adaptation and training, deviating from the intuitive nature of pen-based interfaces.
Innovation Solution
A gaze-based prediction device that combines cursor movement and eye gaze data to predict the intended task by building characteristic curves from user interactions and comparing them to stored profiles, allowing for intuitive task identification and execution without the need for external controls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multi-finger gestures and external buttons are used for pen-based interaction, then device functionality is enhanced, but interaction seamlessness and intuitiveness deteriorate
Solution Approach 1:
The patent replaces mechanical interaction methods (multi-finger gestures, external buttons) with a gaze-based control system. The eye tracker captures gaze information to determine user intent, substituting physical mechanical interactions with optical tracking and computational prediction, thereby maintaining functionality while improving interaction seamlessness
Solution Approach 2:
The patent introduces a prediction model as an intermediary between the user's gaze and the device's response. This model predicts user intent by analyzing gaze patterns and device state, serving as a mediator that translates natural gaze movements into meaningful commands without requiring direct manual interaction
2Adaptability or versatility
If context menus and pop-up menus are used for task execution, then task diversity is increased, but user adaptation time increases
Solution Approach 1:
The patent performs preliminary action by pre-training a prediction model with diverse task patterns and characteristics. The model learns from training data containing various tasks, device states, and gaze patterns, so that when deployed, it can predict user intent without requiring users to adapt to new interaction paradigms or memorize menu structures
Solution Approach 2:
The system performs self-service by automatically adapting to user behavior patterns through the prediction model. The model continuously learns from user interactions and refines its predictions, eliminating the need for users to manually adapt to device-specific gestures and menus
3Adaptability or versatility
If device-specific gestures and controls are implemented, then device functionality is enhanced, but ease of use for new users deteriorates
Solution Approach 1:
The patent implements a universal gaze-based control system that can perform multiple functions across different devices and applications. The eye tracker and prediction model provide a unified interaction paradigm that works regardless of device-specific features, making the system accessible to new users without requiring device-specific training
Data Source
AI summary
The gaze-based prediction device for the prediction of the task that is intended to be performed by the user, includes at least one computer peripheral device for at least the movement of a cursor displayed on a visual display from an initial position to a final position, wherein the computer peripheral device is adapted to collect physical movement information from the user.