Eye Tracking Training System for Object Proficiency Assessment
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Solution Overview
Problem
Existing training systems lack an effective method to assess and improve an individual's proficiency in tracking objects, particularly in sports and tactical scenarios, where quick and accurate visual processing is crucial.
Innovation Solution
A system comprising a delivery device that projects an object toward a target along a trajectory, accompanied by sensors to detect eye characteristics of the trainee and a computing system to determine a score based on the detected eye characteristics, indicating the trainee's proficiency in tracking the object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional training methods are used without objective measurement, then training can be conducted with simple equipment, but the precision and reliability of assessing tracking proficiency is insufficient
Solution Approach 1:
The patent replaces subjective visual assessment and manual tracking evaluation with an automated optical measurement system. Eye tracking cameras and sensors objectively measure gaze position, fixation duration, and saccade patterns, substituting mechanical/manual assessment methods with precise optical detection to quantify tracking proficiency without requiring complex manual evaluation protocols
Solution Approach 2:
The system creates a digital model of the trainee's eye movement patterns by capturing and analyzing gaze data. This digital copy of visual behavior allows for repeated measurement and comparison against performance thresholds, enabling precise assessment of tracking proficiency without requiring physical presence of instructors for evaluation
2Measurement precision
If eye tracking sensors are added to measure proficiency, then assessment accuracy improves, but the complexity and cost of the training system increases
Solution Approach 1:
The eye tracking sensor system serves multiple functions: it detects gaze position, measures fixation duration, tracks saccade patterns, and monitors overall eye movement. This multi-functional capability allows a single sensor integration to provide comprehensive tracking proficiency assessment across different task types and difficulty levels, reducing the need for separate measurement devices for each parameter
Solution Approach 2:
The system uses the trainee's own eye movements as the measurement signal without requiring external assistance. The eye tracker automatically captures and processes gaze data in real-time, enabling self-assessment of tracking ability where the subject's physiological response provides the measurement data, reducing the need for external evaluators or complex testing protocols
3Productivity
If the object size is reduced to increase tracking difficulty, then training effectiveness for small object tracking improves, but the difficulty of detecting and measuring eye characteristics increases
Solution Approach 1:
The system compensates for smaller object sizes by adjusting measurement parameters and analysis thresholds. The eye tracking software is calibrated to detect subtle gaze variations that correspond to tracking small objects, modifying the sensitivity and resolution parameters of eye characteristic detection to maintain measurement accuracy regardless of object scale
Solution Approach 2:
The system transitions from measuring only gaze position to analyzing multiple dimensions of eye characteristics including fixation duration, saccade velocity, pupil dilation, and blink patterns. This multi-dimensional measurement approach provides richer data about tracking effort and proficiency, compensating for the reduced visual signal from smaller objects by examining additional physiological parameters
Data Source
AI summary
A system can include a delivery device that projects an object that is no greater than 1.40 inches in diameter toward a target along a trajectory, a sensor configured to detect eye characteristics of a trainee, and a computing system configured to determine a score of the trainee based upon the detected eye characteristics. A system can include a delivery device that projects an object that is no greater than 1.40 inches in diameter toward a target along a trajectory, a human machine interface (HMI) device that receives an input from a trainee when the trainee identifies an estimated characteristic of the object after the object exits the delivery device, where the HMI device creates a representative signal of the input, and the signal indicates the estimated characteristic to a computing system that can determine a score of the trainee based upon the representative signal.