VR Visual Function Measurement System Using Eye Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for measuring clinical parameters of visual function are subjective, non-reproducible, and do not consider the patient's adaptation capacity, leading to inconsistent results and potential worsening of vision due to unaccounted visual function compensations, and are influenced by the specialist's subjectivity.
Innovation Solution
A system using virtual reality with tracking sensors, a 3D display unit, and movement sensors to create immersive environments for objective measurement and therapy, integrating ocular and visual function parameters, allowing real-time data processing and personalized recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual clinical testing methods are used, then the measuring process is simple to perform, but the results are subjective and non-reproducible
Solution Approach 1:
The patent replaces manual clinical testing with an automated system using video cameras for eye tracking, head orientation sensors, and electronic processing circuits. This substitution eliminates subjectivity by using optical and electronic systems to objectively measure visual function parameters, directly resolving the contradiction between measurement objectivity and system complexity.
2Measurement precision
If independent visual function tests are performed, then each parameter can be measured separately, but the results are not valid because patient adaptation capacity is not considered
Solution Approach 1:
The patent merges multiple visual function tests into a single integrated system that simultaneously measures various parameters while the patient interacts with a virtual reality environment. This allows assessment of adaptation capacity by observing how the patient's visual system responds to complex, multi-parameter stimuli, resolving the contradiction between measurement validity and functional adaptability.
Solution Approach 2:
The system dynamically adjusts test parameters based on real-time patient responses and adaptation patterns. The virtual reality environment can modify stimulus characteristics during testing to assess how the visual system adapts, thereby measuring both individual parameters and their interactions, resolving the contradiction between precise measurement and adaptability assessment.
3Reliability
If traditional clinical testing is used, then the equipment required is simple, but the reproducibility and consistency of results are significantly limited
Solution Approach 1:
The patent replaces manual clinical assessment with automated electronic systems including video cameras, sensors, and processing circuits that objectively capture and analyze visual function data. This substitution ensures reproducible and consistent results by eliminating human subjectivity, directly addressing the contradiction between reliability and system complexity.
4Adaptability or versatility
If immersive virtual reality environments are used, then patient adaptation capacity can be assessed, but the system complexity increases
Solution Approach 1:
The patent creates a multi-functional system where a single virtual reality platform serves multiple purposes: it provides immersive stimulation for assessing adaptation capacity, delivers visual stimuli for various visual function tests, and collects data across multiple parameters simultaneously. This universal approach assesses adaptation capacity without proportionally increasing system complexity, as one system performs multiple functions.
Data Source
Figure 1
Figure 2A~2B
Figure 3A~3B
AI summary
System for integrally measuring clinical parameters of the visual function including a display unit (20) for representing a scene with a 3D object having variable characteristics such as virtual position and virtual volume of the 3D object within the scene; movement sensors (60) for detecting the user head position and distance from the display unit (20); tracking sensors (10) for detecting the user pupils position and pupillary distance; an interface (30) for the user interaction on the scene; processing means (42,44) for analysing the user response based on the data coming from sensors (60,10) and the interface (30), with the characteristics variations of the 3D object; and based on the estimation of a plurality of clinical parameters of the visual function related to binocularity, accommodation, ocular motility and visual perception.