Smartphone Visual Acuity Refractive Error Estimation
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Solution Overview
Problem
Current methods for estimating refractive error outside medical settings are unreliable and require dedicated equipment, making it challenging to accurately determine refractive error without specialized tools or medical training.
Innovation Solution
A device and method that use a smartphone or similar mobile device to measure visual acuity at multiple blur levels, processing this data to estimate refractive error through a specific model derived from a generic model involving theoretical visual acuity, blur data, and refractive error, allowing for accurate estimations without dedicated equipment or medical expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If portable solutions based on visual acuity measurements are used to estimate refractive error outside medical settings, then accessibility and ease of operation are improved, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent applies parameter changes by measuring visual acuity at multiple blur levels (different defocus conditions) rather than a single level, and by capturing multiple measurements to establish statistical relationships. This transforms the estimation process from a simple single-point measurement to a multi-parameter analysis that compensates for the lack of specialized equipment, thereby maintaining measurement precision while preserving accessibility.
Solution Approach 2:
The patent implements preliminary action by establishing a statistical model through multiple reference measurements and blur level assessments before performing the actual refractive error estimation. This preliminary characterization of the user's visual response across different blur conditions creates a baseline that enables accurate subsequent estimations without requiring specialized medical equipment or training.
2Measurement precision
If dedicated equipment and medical training are required for accurate refractive error measurement, then measurement precision is improved, but device complexity and ease of operation worsen
Solution Approach 1:
The patent replaces the mechanical/optical measurement systems (retinoscope, autorefractor) with a computational approach using a standard smartphone camera and screen. Instead of using specialized optical equipment to directly measure refractive error, the system uses the smartphone to present visual acuity tests at different blur levels and processes the results through statistical modeling, thereby eliminating the need for dedicated medical equipment while maintaining measurement capability.
Solution Approach 2:
The patent enables self-service by allowing users to perform their own refractive error assessments using a smartphone without requiring medical professionals to operate specialized equipment. The automated presentation of visual acuity tests at multiple blur levels and the automatic processing of results through the statistical model empower users to conduct their own measurements, eliminating the need for medical training and specialized device operation.
3Measurement precision
If multiple visual acuity measurements at different blur levels are taken, then refractive error estimation accuracy is improved, but measurement time and device complexity increase
Solution Approach 1:
The patent applies periodic action by systematically presenting visual acuity measurements at discrete, predetermined blur levels in a structured sequence. This periodic sampling of visual acuity across different defocus conditions allows the system to capture the necessary data points for accurate statistical modeling while maintaining a efficient measurement rhythm that minimizes total testing time compared to continuous or random measurement approaches.
Data Source
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AI summary
A refractive error of an eye of a user is estimated by receiving measurements (21) of the visual acuity, VA, of the user's eye, called reference VA measurements, and data (22) related to distinct respectively associated levels of blur, called reference blur data, the reference VA measurements being performed within a reference measurement period by imposing the respective levels of blur on the user's eye. A generic model (23) involving a theoretical VA, theoretical blur data and a theoretical refractive error is particularized into a specific model (24) for the user's eye, from the reference VA measurements and the reference blur data, and information (25) relevant to the refractive error of the user's eye is produced from the specific model and provided. Applications to vision follow-up and to myopia, hyperopia and astigmatism control.