Eye Tracking Evaluation via Visual Cue Scoring
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Solution Overview
Problem
There is a need for systems and methods to evaluate human eye movement, track and score individuals' eye movements, and recommend training tasks to improve visual search and other eye movements.
Innovation Solution
The system and method involve receiving data on eye location and movement, identifying temporal or biomechanical phases of a task, identifying visual cues within these phases, and scoring the eye tracking by comparing the data to the visual cues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If eye movement tracking systems are implemented to evaluate visual search patterns, then measurement precision of eye movement is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical eye tracking systems with computational image processing methods. Video cameras capture eye movements, and software algorithms analyze the visual search patterns, substituting mechanical tracking apparatus with digital processing to achieve precise measurement while reducing physical system complexity
Solution Approach 2:
The system creates digital copies of eye movement data through video recording and image capture. By capturing visual information as digital images and analyzing them computationally, the system achieves precise measurement of eye movements without requiring complex real-time mechanical tracking devices
2Measurement precision
If detailed eye movement data collection is performed to improve cognitive evaluation accuracy, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs continuous eye movement tracking during natural task performance rather than requiring separate measurement sessions. Video cameras continuously capture eye movements as individuals perform cognitive tasks, allowing simultaneous data collection and evaluation without interrupting the useful action, thereby reducing time loss while maintaining measurement precision
Solution Approach 2:
The system pre-processes and stores video data during task performance, preparing eye movement data for analysis in advance. By capturing and organizing data continuously during natural behavior, the system eliminates time-consuming post-hoc data collection procedures while ensuring high measurement precision through comprehensive data capture
3Productivity
If systematic visual search pattern analysis is implemented to evaluate expert performance, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex analytical frameworks with computational image processing algorithms. Software automatically analyzes visual search patterns from video data, identifying expert vs. novice patterns through digital processing rather than manual assessment, thereby improving evaluation productivity while reducing the complexity of the analytical system
Solution Approach 2:
The system enables automatic self-analysis of eye movement data through computational algorithms. The software independently processes video recordings, identifies visual search patterns, and generates evaluations without requiring complex external analytical tools or manual intervention, improving productivity while keeping the system relatively simple
Data Source
AI summary
Systems and methods are disclosed for evaluating human eye tracking. One method includes receiving data representing the location of and/or information tracked by an individual's eye or eyes before, during, or after the individual performs a task; identifying a temporal phase or a biomechanical phase of the task performed by the individual; identifying a visual cue in the identified temporal phase or biomechanical phase; and scoring the tracking of the individual's eye or eyes by comparing the data to the visual cue.