Ophthalmic Light Source Brightness Monitoring via Spot Image Feedback
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Solution Overview
Problem
Existing ophthalmic laser systems do not regularly monitor the brightness of their light sources, leading to potential issues with light degradation that may not be detected until servicing or during procedures, which can impact surgical precision and patient safety.
Innovation Solution
A system that automatically monitors the brightness of light sources by directing light towards a test target, analyzing digital images of the actual spot, and comparing actual brightness parameters to expected parameters to detect deviations, providing notifications or adjustments as needed, and analyzing historical data for trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If light sources are used in ophthalmic laser systems for illumination and auxiliary light, then the system can perform surgical procedures, but the light sources may degrade over time leading to brightness deviations that compromise surgical precision and patient safety
Solution Approach 1:
The system performs preliminary brightness monitoring by directing light through the light source onto a test target and capturing images with a digital camera before actual surgical procedures. This allows detection of brightness degradation trends early in the light source lifespan, enabling preventive maintenance before the degradation affects surgical precision or patient safety.
Solution Approach 2:
The system establishes a feedback loop where the computer continuously monitors brightness parameters by comparing actual brightness measurements (from digital images) against expected brightness values. When deviations are detected, the system can alert operators or adjust parameters, creating a closed-loop monitoring system that maintains reliability throughout the light source operational life.
2Productivity
If manual monitoring of light source brightness is performed during servicing, then some level of oversight is achieved, but continuous monitoring is not possible and issues are detected too late
Solution Approach 1:
The system performs self-monitoring by automatically directing light through the light source onto a test target, capturing images, and analyzing brightness parameters without requiring manual intervention. The computer executes the entire monitoring process autonomously, eliminating the need for manual servicing while providing continuous oversight, thus improving productivity and eliminating time loss associated with manual checks.
3Reliability
If the system monitors brightness by capturing digital images and analyzing pixel values, then continuous monitoring is enabled, but the device complexity increases
Solution Approach 1:
The system uses existing components (digital camera, computer) for multiple functions: the digital camera captures both test target images for brightness monitoring and can potentially capture surgical field images, while the computer performs both brightness analysis and surgical control functions. This multi-functionality reduces the need for dedicated monitoring hardware, thereby limiting the increase in device complexity while maintaining continuous monitoring capability.
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
Enables continuous monitoring and adjustment of light source brightness, preventing degradation, ensuring consistent illumination for surgical procedures and detecting potential medical conditions in patients.
Implementation Method 1
The light system directs light towards a test target located at a target plane according to an expected parameter set to yield an actual spot on the test target
Data Source
AI summary
In certain embodiments, an ophthalmic system includes a light system, an imaging system, and a computer. The light system directs light towards a test target according to an expected parameter set to yield an actual spot on the test target. Each expected brightness parameter of the set describes an expected brightness of the actual spot. The imaging system generates a digital image of the actual spot. The computer determines pixel values of the pixels of the digital image and determines an actual brightness parameter set according to the pixel values. Each actual brightness parameter of the set describes an actual brightness of the actual spot and corresponds to an expected brightness parameter. The computer compares the actual brightness parameters to the corresponding expected brightness parameters and detects a deviation. The computer identifies an issue of the light system indicated by the deviation and provides an output associated with the issue.