Remote Visual Acuity Examination System Using Real-Time Feedback
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Solution Overview
Problem
Existing computerized eye examinations are overly complex and time-consuming, providing an unsatisfactory user experience due to technical deficiencies such as insufficient data, ambiguous results, and lack of real-time feedback, which contrasts with traditional in-person examinations.
Innovation Solution
A computerized visual acuity examination system using a personal computing device with a camera, microphone, and display screen, providing real-time feedback and sophisticated data processing to enhance examination reliability, allowing users to take tests without an in-person professional, with results reviewed by medical professionals for prescription updates and potential in-person assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If computerized eye examinations are conducted without in-person professional administration, then convenience and accessibility are improved, but reliability and data quality deteriorate due to insufficient examination results data and ambiguous examination results data
Solution Approach 1:
The system provides real-time feedback to users during the examination process, guiding them on proper device positioning, lighting conditions, and examination procedures. This feedback mechanism ensures that users can conduct reliable examinations at home without professional administration, resolving the contradiction between convenience and reliability.
Solution Approach 2:
The patent introduces an intermediary processing system that uses image analysis and machine learning algorithms to evaluate examination quality, detect anomalies, and validate results. This intermediary layer ensures data reliability while maintaining the convenience of remote examination by automatically filtering and verifying user-generated examination data.
2Loss of time
If computerized eye examinations are conducted without in-person professional administration, then time consumption is reduced, but data quality and result accuracy worsen due to lack of verification of conditions suitable for unassisted computerized eye examination
Solution Approach 1:
The system performs preliminary checks and validations before conducting the actual visual acuity measurement, ensuring that environmental conditions, device positioning, and user readiness are appropriate. This preliminary action guarantees measurement accuracy while maintaining rapid examination throughput without requiring in-person professional verification.
Solution Approach 2:
The patent replaces the mechanical system of in-person professional administration with an automated digital system using image processing, computer vision, and machine learning algorithms. This substitution maintains measurement precision by using sophisticated algorithms to verify examination conditions and validate results, while dramatically reducing time consumption and eliminating the need for in-person visits.
3Reliability
If sophisticated processing of eye examination data is implemented, then reliability of processed data is improved, but device complexity and computational requirements worsen
Solution Approach 1:
The data processing system is segmented into modular components: image acquisition module, preprocessing module, feature extraction module, analysis module, and validation module. Each module performs a specific function and can be independently optimized, reducing overall system complexity while maintaining high reliability through specialized processing at each stage.
Solution Approach 2:
The patent uses digital copies and simulations of optical measurement processes, replacing complex physical measurement systems with computational models. This allows sophisticated data processing to be performed using software algorithms rather than complex hardware, reducing device complexity while maintaining or improving measurement reliability through flexible computational analysis.
Data Source
AI summary
Systems and methods for assessing the visual acuity of person using a computerized consumer device are described. The approach involves determining a separation distance between a human user and the consumer device based on an image size of a physical feature of the user, instructing the user to adjust the separation between the user and the consumer device until a predetermined separation distance range is achieved, presenting a visual acuity test to the user including displaying predetermined optotypes for identification by the user, recording the user's spoken identifications of the predetermined optotypes and providing real-time feedback to the user of detection of the spoken indications by the consumer device, carrying out voice recognition on the spoken identifications to generate corresponding converted text, comparing recognized words of the converted text to permissible words corresponding to the predetermined optotypes, determining a score based on the comparison, and determining whether the person passed the visual acuity test.