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当前对比敏感度临床测试的有效性及其预测低视力患者阅读速度的能力。

The validity of current clinical tests of contrast sensitivity and their ability to predict reading speed in low vision.

作者信息

Leat S J, Woo G C

机构信息

Centre for Sight Enhancement, School of Optometry, University of Waterloo, Ontario, Canada.

出版信息

Eye (Lond). 1997;11 ( Pt 6):893-9. doi: 10.1038/eye.1997.228.

Abstract

PURPOSE

Contrast sensitivity (CS) testing using chart tests of CS is becoming increasingly common in low vision assessment. Yet we know little about the validity of these charts, i.e. which region of the spatial frequency spectrum is being measured. In this study we aimed to determine the validity of currently available CS charts by comparison against oscilloscope-based CS. We also determined their relative ability to predict reading speed.

METHODS

CS was measured with five commercially available charts and the contrast sensitivity function was determined with sinusoidal gratings presented on a Joyce screen using a two-alternative forced choice staircase technique in 36 observers with low vision and 3 with normal vision. Reading rate was also measured with the subject reading with his or her own optical low vision aid.

RESULTS

The results show that the Pelli-Robson chart and the Cambridge gratings are good measures of medium to low spatial frequencies, as would be predicted from their design, while the Regan and UW charts correlated with medium to high frequencies. The Vistech chart was a good predictor of CS at each spatial frequency.

CONCLUSIONS

The best chart test of CS depends on which region of the CS curve is of interest. All the charts were good predictors of reading rate.

摘要

目的

在低视力评估中,使用图表测试对比敏感度(CS)正变得越来越普遍。然而,我们对这些图表的有效性知之甚少,即它们测量的是空间频谱的哪个区域。在本研究中,我们旨在通过与基于示波器的CS进行比较,确定当前可用CS图表的有效性。我们还确定了它们预测阅读速度的相对能力。

方法

使用五种市售图表测量CS,并在36名低视力观察者和3名正常视力观察者中,采用二选一强制选择阶梯技术,在乔伊斯屏幕上用正弦光栅确定对比敏感度函数。阅读率也通过受试者使用其自己的光学低视力辅助工具进行测量。

结果

结果表明,佩利 - 罗布森图表和剑桥光栅是中低频的良好测量指标,正如从其设计所预测的那样,而里根图表和华盛顿大学图表与中高频相关。维斯特ech图表是每个空间频率下CS的良好预测指标。

结论

CS的最佳图表测试取决于CS曲线中感兴趣的区域。所有图表都是阅读率的良好预测指标。

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