Eye-Tracking Concussion Detection Using Baseline Ocular Responses
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Solution Overview
Problem
Current methods for detecting concussions and other metabolic disorders in the brain lack reliability and objectivity, particularly in field settings, and existing tests do not provide immediate and accurate assessments.
Innovation Solution
The methods and systems utilize eye function and morphology changes caused by perturbations in glucose and oxygen levels in the brain to detect diseases such as concussions, using eye movement tests and imaging to identify alterations in eye movements and structures, which are then compared to baseline readings or group norms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If medical examination methods are used to detect concussions, then detection can be performed outside medical facilities, but the reliability and objectivity of detection deteriorates due to subjectivity and lack of baseline information
Solution Approach 1:
The system performs preliminary baseline testing during pre-season or before athletic events to establish each individual's normal eye movement patterns. This baseline data is stored and used for comparison during in-field testing, enabling reliable concussion detection without requiring medical professionals or complex equipment during actual gameplay or training sessions.
2Reliability
If CT scans are used to detect brain damage, then detection accuracy is improved, but the device availability deteriorates as it is not readily available outside medical facilities
Solution Approach 1:
The invention extracts the essential diagnostic function from complex medical imaging equipment by using simple, portable eye-tracking technology that can be deployed in the field. The system captures eye movement data using basic optical sensors and cameras, processes this data through algorithms comparing against baseline patterns, and provides concussion detection results without requiring CT scanners or other heavy medical equipment.
3Productivity
If conventional concussion tests are administered, then detection can be performed, but the measurement precision deteriorates due to poor concurrent validity and lack of established baseline scores
Solution Approach 1:
The system implements feedback by continuously comparing real-time eye movement measurements against stored baseline data for each individual. This comparison provides objective feedback on deviations from normal patterns, enabling precise measurement of concussion effects. The feedback mechanism includes quantitative metrics such as saccade velocity, fixation duration, and smooth pursuit accuracy, which are compared to baseline values to determine the presence and severity of concussion.
Data Source
AI summary
Disclosed herein are systems and methods for the detection of neurological condition in a subject. The disclosed methods and systems provide, in certain embodiments, providing optical stimuli to a subject via a graphical display, capturing, using a camera, a plurality of images of eyes of the subject when the optical stimuli is provided to the subject via the graphical display, determining, by a processor, an occurrence of one or more ocular responses of structures of the eyes based on the plurality of images, identifying, by the processor, an occurrence of a neurological condition in the subject based on the one or more ocular responses, and providing the identification of the occurrence of the neurological condition to the subject via a graphical user interface.