Methods and kits for assessing neurological and ophthalmic function and localizing neurological lesions
Inventors
Assignees
New York University • United States Department of Veterans Affairs
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Publication Number
US-12635957-B2
Publication Date
2026-05-26
Expiration Date
Abstract
A method for detecting, diagnosing or screening for concussion in a subject includes a) tracking eye movement of at least one eye of the subject, b) analyzing eye movement of at least one eye of the subject, c) calculating a statistical test for eye movement of at least one eye of the subject as compared to a normal or mean eye movement, and d) detecting, diagnosing or screening for an impairment based on the calculated statistical test.
Core Innovation
The invention provides an eye-tracking based framework for assessing neurological and ophthalmic function by tracking binocular pupil behavior during a moving video visual stimulus. It uses eye movement tracking of a right eye and a left eye with pupil position x/y coordinates, and it includes temporal calibration rather than spatial calibration. The captured data is preprocessed and normalized prior to metric computation.
Multiple eye-movement metrics are computed from the tracked pupil data, including segment variances and variance-related measures for gaze behavior. The framework includes statistical comparisons of one or more individual metrics against a normal or mean value, and it computes quantities such as standard deviation and p-values. Additional derived characteristics include skew and box dimensions, and conjugacy and disconjugacy measures are computed using variance of left-right pupil differences.
The disclosed approach links abnormal metric patterns to impairment and dysfunction, including cranial nerve dysfunction (II/III/IV/VI) and increased intracranial pressure. It is described for concussion, subconcussion, and blast injury including radiographically silent cases, and it includes localization and quantitation of central nervous system lesions based on side-specific or asymmetry patterns. The framework is presented as a system including a kit and a computer system context, with clinical and experimental context including test-retest reliability and examples.
Claims Coverage
The independent claim covers a method for detecting, diagnosing, or screening for concussion using an eye tracker with a display-based video stimulus, binocular pupil tracking, calculation of selected eye-movement metrics, and a statistical test against normal or mean values followed by impairment detection based on the test result. The inventive features include the selection of specific variance and conjugacy metrics and the use of a statistical test versus normal or mean values.
Binocular video-based eye tracking for concussion screening
Seating a subject in front of a display, presenting a video for the subject to watch on the display, and tracking eye movement of a right eye and a left eye using an eye tracker to track pupil positions for at least thirty seconds at a frequency of at least 500 Hz.
Selected eye-movement metrics based on segment variance and conjugacy
Analyzing eye movement by calculating one or more individual metrics relating to eye movement selected from right and left segment and total X- or Y-coordinate variance metrics, and conjugacy metrics including conjugacy in the X-coordinate and conjugacy of specific segments in the X- and Y-coordinates.
Statistical test against normal or mean values for impairment detection
Calculating a statistical test for the one or more individual metrics as compared to a normal or mean value of the one or more individual metrics, and detecting, diagnosing or screening for an impairment based on the calculated statistical test.
Across the independent claim, the inventive coverage is defined by binocular eye-tracking during a video stimulus, computing a defined set of segment-variance and conjugacy metrics, and using a statistical test versus normal or mean metric values to detect or screen for concussion-related impairment.
Stated Advantages
Provides feasibility of uncalibrated tracking for detecting, diagnosing or screening for concussion across subject groups.
Enables distinguishing between group differences using multiple eye-tracking parameters and statistical measures.
Supports correlations with validated concussion outcomes (SCAT/SAC).
Allows detecting, diagnosing or screening for concussion in a subject based on calculated statistical tests from eye-movement metrics.
Documented Applications
Use in a study context to detect, diagnose or screen for concussion in healthy volunteers and patient groups including TBI/concussion and non-brain injuries, using uncalibrated eye-movement metrics and statistical testing.
Detecting, diagnosing, or screening for concussion in a subject.
Assessing concussion, subconcussion, and blast injury, including radiographically silent cases, using eye-movement metrics.
Localization and quantitation of central nervous system lesions based on side-specific or asymmetry patterns.
Detecting impairment related to cranial nerve dysfunction (II/III/IV/VI) and increased intracranial pressure in the disclosed clinical and experimental context.
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