Eye Blink Metrics for Rapid Concussion Detection
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Solution Overview
Problem
Concussions are difficult to diagnose quickly and effectively, and there is a need for improved methods and systems to detect their occurrence and assess their severity.
Innovation Solution
A method and system that captures eye blink data, analyzes it to generate specific metrics, and compares these metrics to predefined normal values to identify and quantify concussions using an eye tracking device and computer processor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional concussion diagnosis methods are used, then diagnostic accuracy may be maintained, but diagnostic speed and efficiency deteriorate
Solution Approach 1:
The patent replaces traditional mechanical/physical examination methods with an optical-based eye tracking system. The system uses eye trackers to capture blink data and generates metrics such as blink rate, blink duration, and inter-blink intervals to objectively detect and quantify concussions, enabling rapid automated assessment without relying on subjective clinical evaluation
Solution Approach 2:
The patent transforms the diagnosis approach by changing from assessing traditional clinical parameters to measuring ocular parameters. Specifically, it monitors blink rate, blink duration, and inter-blink intervals as biomarkers for concussion detection, providing quantifiable metrics that enable faster and more objective diagnosis
2Measurement precision
If detailed concussion assessment is performed, then diagnostic accuracy improves, but time consumption increases
Solution Approach 1:
The patent implements a tiered assessment approach where essential concussion detection is achieved through a limited set of key eye blink metrics. The system can provide rapid screening using primary metrics (blink rate, duration) and optionally expand to more comprehensive analysis if needed, allowing clinicians to balance speed and detail based on situational requirements
Solution Approach 2:
The system performs preliminary concussion screening through automated eye blink analysis before more detailed clinical evaluation. By quickly generating objective metrics from eye tracking data, it provides an initial assessment that guides subsequent diagnostic steps, reducing overall diagnostic time while maintaining accuracy
Data Source
AI summary
A method for identifying an occurrence of a concussion in a subject involves capturing eye blink raw data from at least one eye of the subject. The method next involves analyzing the eye blink raw data to generate at least a first subject specific eye blink metric and determining that a significant difference exists between the first subject specific eye blink metric and a predefined normal value. Next, the occurrence of the concussion in the subject may be identified, based on determining that the significant difference exists.