Smartphone Pupillary Light Reflex Detection for Impairment Assessment
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Solution Overview
Problem
There is a need for a non-invasive, portable method to detect cognitive impairment caused by alcohol, drugs, or fatigue, as individuals may not recognize their own impairment, and existing methods are not easily accessible or accurate for self-assessment.
Innovation Solution
A system and method using a portable video capture device (PVCD) to measure pupillary light reflex and other involuntary eye movements, correlating these measurements with impairment levels, and implementing a smart user interface to collect user data and estimate Blood Alcohol Concentration (BAC) values, with the option to connect to emergency services for assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dedicated instrument like a breath analyzer or pupillometer is used to assess impairment, then measurement precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent applies universality by implementing multiple impairment detection functions within a single smartphone application. The system measures pupillary light reflex, tracks eye movement, and estimates blood alcohol concentration using only the smartphone's existing camera and sensors, eliminating the need for multiple dedicated instruments while maintaining comprehensive assessment capabilities
Solution Approach 2:
The patent uses copying by replicating the functionality of specialized medical instruments through software-based measurement. The smartphone camera captures and analyzes pupillary responses and eye movements, creating a digital copy of pupillometer and breathalyzer functions that achieves sufficient measurement precision for impairment assessment without requiring physical dedicated devices
2Measurement precision
If professional impairment testing equipment is deployed, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical and optical measurement systems with computational methods. Instead of using complex pupillometers and breath analyzers, the system uses the smartphone's camera to capture visual data of pupillary light reflex and eye movement, then applies image processing algorithms and correlation analysis to achieve accurate impairment detection through software rather than specialized hardware
Solution Approach 2:
The patent applies parameter changes by transforming physical measurements into computational parameters. The system converts pupillary diameter measurements, eye movement trajectories, and response timing into standardized parameters that can be correlated with impairment levels using reference datasets, enabling complex assessment through simplified computational processing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides a quick, accurate, and accessible means to assess cognitive impairment, enabling users to determine their own impairment levels and connect with transportation or emergency services as needed, enhancing safety and liability in public transportation environments.
Implementation Method 1
uses a free-hand portable testing apparatus to detect involuntary eye movement or reflex that are affected by fatigue, the consumption of alcohol, drugs, or trauma
Data Source
AI summary
A system and method are provided for optical detection of cognitive impairment of a person using a portable video capture device (PVCD). In one embodiment, the method includes: (i) capturing video of an eye exposed to light stimuli over a predetermined time using a video camera of the PVCD; (ii) processing the video to locate at least one feature of the eye; (iii) measuring a change in the feature in response to the light stimuli; (iv) analyzing data from the measured change in the feature by extracting data from the measured change in the feature, calculating a number of parameters from the extracted data, correlating the calculated parameters with predetermined reference parameters and predicting a degree of impairment based on the results of the correlation; and (v) outputting through a user interface in the PVCD the degree of impairment to a user. Other embodiments are also described.