Eye Tracking Text Interaction via Physiological Data Analysis
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Solution Overview
Problem
Current systems fail to accurately determine a user's intent while interacting with electronic content, leading to suboptimal user experiences and limited accessibility for users who cannot perform traditional input actions.
Innovation Solution
The use of physiological data, such as gaze characteristics and reading pace, to predict interaction events, allowing for the initiation of interactions without traditional input methods, and incorporating machine learning models to refine these predictions based on user-specific actions and context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional input methods (mouse click, gesture) are used for text selection, then interaction precision is improved, but accessibility for users with disabilities deteriorates
Solution Approach 1:
The patent replaces mechanical input methods (mouse clicks, gestures) with physiological signal-based interaction. Eye tracking cameras capture pupil movements and gaze characteristics to determine user intent, substituting physical mechanical actions with biological signal detection. This enables users with motor disabilities to interact with text elements through natural eye movements without requiring manual input devices.
2Adaptability or versatility
If physiological data collection is implemented, then accessibility for users with disabilities is improved, but device complexity deteriorates
Solution Approach 1:
The patent implements multi-functionality by using eye tracking technology for multiple purposes: (1) determining user intent for text selection, (2) measuring reading pace and comprehension, (3) detecting engagement level, and (4) providing accessibility for users with motor disabilities. This single physiological measurement system serves multiple functions, reducing the need for separate complex input devices for each function.
3Ease of operation
If automated interaction initiation is implemented, then ease of operation is improved, but reliability deteriorates due to false activations
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors physiological data (pupil dilation, gaze position, reading pace) and adjusts interaction initiation thresholds based on user behavior patterns. The system learns individual user characteristics and provides feedback loops to distinguish between intentional interactions (focusing on text elements for extended periods) and incidental physiological responses, thereby reducing false activations while maintaining ease of operation.
Data Source
AI summary
Various implementations disclosed herein include devices, systems, and methods that determine whether the user is reading text or intends an interaction with a portion of the text in order to initiate an interaction event during the presentation of the content. For example, an example process may include obtaining physiological data associated with an eye of a user during presentation of content, wherein the content includes text, determining whether the user is reading a portion of the text or intends an interaction with the portion of the text based on an assessment of the physiological data with respect to a reading characteristic, and in accordance with a determination that the user intends the interaction with the portion of the text, initiating an interaction event associated with the portion of the text.