System and method for detecting neurological disorders and for measuring general cognitive performance
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Publication Number
US-12165770-B2
Publication Date
2024-12-10
Expiration Date
Abstract
Methods and systems useful for detecting neurological disorders and for measuring general cognitive performance, in particular by measuring eye movements and/or pupil diameter during eye-movement tasks.
Core Innovation
The invention provides a system for detecting one or more cognitive disorders that include middle temporal lobe alterations in a subject. The system measures eye movements while the subject is binding visual features and measures pupil diameters, using an eye tracker and a means for measuring pupil diameters for the same subject during the binding visual features activity.
A processor receives the eye-tracking data and the pupil diameter data and analyzes both to generate a detection of one or more cognitive compromises. The processor reports cognitive compromises in specific cognitive domains, including at least visual working memory capabilities of the subject, and the report is displayed using a display means configured to display the test report received from the processor.
In embodiments covered by the relevant claims, the processor further analyzes eye-tracking and pupil diameter data to classify eye movement features and pupil behavior using an intelligent algorithm. The system reports cognitive performance and/or a pathological index classification, including a compound value within the pathology, based on the classifier output derived from the measured eye movement features and pupil behavior.
The document also describes comparisons with a control group and a pupil response condition tied to stronger versus reduced/minimal cognitive effort activities to support domain-specific compromise reporting and compromise interpretation.
Claims Coverage
Independent claim clm-00001 defines the core system architecture and the domain-specific compromise detection reported in a test report. Four additional inventive features are supported across the dependent claims, including control-group and stronger-versus-reduced effort comparisons, classifier-based pathological indexing with a compound value, expanded intelligent-algorithm inputs for binding evaluation, and domain/neurobiological interpretations tied to measured eye and pupil metrics.
System for binding visual features using eye tracker and pupil diameter measurement
A system that detects one or more cognitive disorders including middle temporal lobe alterations by measuring eye movements while the subject is binding visual features, comprising an eye tracker, a means for measuring pupil diameters, a processor configured to receive eye-tracking data and pupil diameter data, and a display means configured to display a test report received from the processor; wherein the processor analyzes the eye-tracking and pupil diameter data and reports detections of cognitive compromises in specific cognitive domains including at least visual working memory capabilities.
Control-group comparison and stronger versus reduced cognitive effort pupil response
A system configured so that the processor uses eye-tracking and pupil diameter measurements to generate reports by comparing the subject values to a control group and by assessing whether pupil diameter increases during activities requiring stronger cognitive effort versus activities requiring reduced/minimal cognitive effort.
Classifier-based pathological index including a compound value within pathology
A system configured to identify and classify eye movement features and pupil behavior from the received eye-tracking data and pupil diameter data and to generate a classifier output for reporting cognitive performance and/or pathological index classification, including a compound pathology value reflecting the level of compromise within that pathology.
Intelligent algorithm inputs using binding evaluation task features and subject information
An intelligent algorithm configured to read input data selected from ocular fixation measures, binding trial identification measures, behavioral response measures, pupil/eye-movement measures, microsaccades, Factors of Form (FF), eye position measures, fixation sequence and fixation timing measures, and subject information such as age, years of education, sex, ethnic group, occupation, and hours per week of physical activity during a Binding Evaluation/Binding Task, for generating the reporting outputs.
Domain and neurobiological interpretation from gaze, ocular fixation, and pupil diameter comparisons
A system that measures gaze duration, ocular fixations, and pupil diameter during feature-binding tasks and reports detected compromises in visual working memory and executive functions, and alterations in the locus coeruleus and noradrenergic system, based on comparisons to a control group and on whether pupil diameter increases during stronger cognitive effort.
Across the independent claim and dependent claims, the inventive coverage centers on detecting cognitive compromises by jointly analyzing eye movements during binding visual features and pupil diameter, reporting domain-specific compromise detections in a test report, optionally using control-group comparisons and stronger-versus-reduced effort pupil behavior, and further extending to classifier-based pathological indexing with expanded intelligent-algorithm inputs and neurobiological interpretation.
Stated Advantages
Detects one or more cognitive compromises in specific cognitive domains, including visual working memory capabilities.
Reports cognitive compromises in specific cognitive domains in a test report displayed to the user.
Enables detection of compromises by comparing measured pupil diameter responses under stronger versus reduced/minimal cognitive effort and comparing subject values to a control group.
Provides classifier-based pathological index classification including a compound pathology value within the pathology.
Supports reporting of cognitive performance and/or pathological index classification using an intelligent algorithm based on eye movement features and pupil behavior.
Documented Applications
Detecting cognitive disorders and cognitive compromises during binding visual features tasks using eye movements and pupil diameter measurements, including cognitive domain assessments such as visual working memory capabilities.
Assessing cognition and pathology-related compromises using control group comparisons and pupil response behavior during activities requiring stronger versus reduced/minimal cognitive effort.
Evaluating specific neurological disorder contexts and cognitive task contexts described in the document, including mild AD patients versus healthy controls and PD/ADHD versus controls, using example test results (Table 1 and Table 2).
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