VR Eye-Tracking for REM Sleep and Ocular Condition Detection
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Solution Overview
Problem
Existing VR technology lacks the capability to effectively diagnose and monitor various ocular conditions such as eye misalignment, macular degeneration, tear film characteristics, floater characteristics, and retinal disorders, relying on invasive and time-consuming methods.
Innovation Solution
Implementing high-resolution VR headsets equipped with advanced eye-tracking sensors and specialized software algorithms to conduct immersive visual tests, analyzing gaze, pupil response, and tear film dynamics, and monitoring REM sleep patterns to detect and monitor ocular conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional diagnostic methods are used for ocular conditions, then diagnostic capability is limited, but the methods are invasive and time-consuming
Solution Approach 1:
The patent replaces traditional mechanical and chemical diagnostic methods (eye drops, physical examinations) with a virtual reality-based optical and computational system. The VR system uses eye-tracking sensors, visual stimuli presentation, and algorithmic analysis to diagnose ocular conditions without physical intervention, thereby eliminating invasiveness while maintaining or improving diagnostic reliability
Solution Approach 2:
The patent creates a virtual copy of the diagnostic environment through VR technology. Instead of physically examining the patient's eyes in a clinical setting, the system renders virtual visual stimuli and captures eye responses through sensors, creating a digital replica of the diagnostic process that is both faster and less invasive than traditional methods
2Measurement precision
If VR technology is used to monitor eye movements, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The patent integrates multiple diagnostic functions into a single VR system. The same VR headset and eye-tracking sensors used for immersive experiences are leveraged to perform various ocular diagnostics including eye movement tracking, visual acuity testing, and detection of ocular conditions, thereby managing complexity through multi-functionality rather than requiring separate specialized devices for each test
Solution Approach 2:
The VR system performs self-calibration and automated analysis of eye movement data. The algorithms automatically process the captured eye-tracking information to detect patterns indicative of ocular conditions, reducing the need for complex manual calibration procedures and expert intervention, thereby managing system complexity through automation
3Measurement precision
If detailed visual patterns are used for macular degeneration detection, then early detection capability is enhanced, but test complexity increases
Solution Approach 1:
The patent employs dynamic visual stimuli that change over time within the VR environment. The visual patterns presented for macular degeneration detection are not static but evolve dynamically, allowing the system to assess multiple aspects of retinal function through a single integrated test sequence, thereby enhancing detection capability without proportionally increasing test complexity
Solution Approach 2:
The VR system continuously presents visual stimuli and continuously tracks eye responses throughout the testing period. This continuous data collection allows for comprehensive assessment of macular function through pattern recognition over time, improving early detection accuracy while maintaining a streamlined continuous testing process rather than requiring multiple discrete tests
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 non-invasive, accurate, and timely detection and monitoring of ocular conditions, enabling early intervention and improving patient outcomes through user-friendly systems suitable for clinical and remote telemedicine applications.
Implementation Method 1
Eye-tracking technology allows systems to detect and respond to where the user is looking
Implementation Method 2
The VR headset projects a series of intricate visual stimuli designed to test various aspects of visual acuity and retinal function
Implementation Method 3
The eye-tracking sensors continuously monitor the patient's gaze, pupil response, and micro-movements to detect abnormalities
Data Source
AI summary
A patient's rapid eye movements (REM) can be evaluated via a virtual reality (VR) system, which can include a VR headset in electronic communication with a computing device. The patient can don the VR headset while she is sleeping. Optionally, the VR system can be used in a home setting, where the patient will likely be able to recreate her usual sleep patterns. Using varying combinations of sensors and cameras, the VR headset tracks the patient's eye movements while she sleeps to identify different sleep stages, including REM periods. Observing the patient's sleep patterns provides great insight into her health as well as opportunities to improve sleep.