研究目的
To present a home-based visual field examination method and evaluate its reliability by comparing with the Humphrey perimeter for glaucoma screening.
研究成果
The home-based visual field test shows reliable ROC characteristics compared to the Humphrey perimeter, making it a useful, low-cost tool for glaucoma screening without specialized equipment. It is simple, fast, and can be performed at home, potentially increasing screening accessibility.
研究不足
The main limitation is that many older people may not be familiar with using computers, requiring assistance. The test is intended for screening and not for monitoring progression of diagnosed cases. Differences in hardware and algorithms compared to standard perimeters may affect results.
1：Experimental Design and Method Selection:
The study used proprietary software implementing a supra-threshold visual field test algorithm at three threshold levels (-4 dB, -8 dB, -12 dB) for the central 24° (52 points) of the visual field. The software compensates for display differences using trigonometry to mimic a classical bowl perimeter. It includes features like a web camera as a virtual photometer to detect ambient luminosity, an expert system for result validation, and the ability to combine multiple tests for higher accuracy.
2：Sample Selection and Data Sources:
Ten patients (20 eyes) were selected, with 1,040 visual field test points compared point-to-point with results from the Humphrey perimeter. Patients were tested consecutively within hours at the glaucoma department.
3：List of Experimental Equipment and Materials:
A 22-inch LCD monitor, virtual reality glasses with a 6-inch Android smartphone, web camera, and the proprietary software were used. The Humphrey perimeter was used as the gold standard.
4：Experimental Procedures and Operational Workflow:
Patients sat in front of a screen or used VR glasses, stared at a central fixation point, and clicked a mouse when they saw stimuli. Room luminosity was checked with the web camera. Each eye was tested separately with near correction if needed. The software adjusted for distance and validated test reliability.
5：Data Analysis Methods:
ROC curves and AUC were calculated using easyROC, an interactive web tool with R, to determine diagnostic accuracy and optimal cut-off points. Reliability indices (fixation losses, false positives, false negatives) were also computed.
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