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Abstracts for Vision 2002

Abstract number: P 10 

DOES CHARACTER-BASED CSF MEASUREMENT MATCH WITH SINE WAVE MESUREMENT IN NORMAL AND LOW VISION?

C Arai¹, A Arditi²
¹National Institute of Special Education, Section of Low vision, Yokosuka, Japan; ²IBM TJ Watson Research Center, Accessibility Research, Hawthorne, NY, United States

Purpose: Contrast Sensitivity Function (CSF) provides more comprehensive information about visual functions than simple visual acuity does for patients with low vision. Although most CSF tests use sine wave targets, it is difficult to apply its results to reading task of low vision patients. We developed a new contrast test chart which use characters instead of sine waves. The purpose is to compare CSF data between the conventional sine wave method and our new method.

Method: Forty four normal subjects and thirty five subjects with low vision were measured their visual acuity, CSF (frequency 1.25, 2.5, 5, 10 cycles per degree;cpd) with sine wave targets, and CSF with our new chart. Sine wave targets were presented in Best-PEST method by PSYCHO computer program. Our new chart consisted of characters in a wide range of contrasts with 0.5 log step. There were 3 characters in the same contrast in each line on the chart. Subject's task was to read characters in each line aloud and when two characters were correctly read, next line of characters in lower contrast was tested. Since the chart was printed only in one character size, observation distance was adjusted to measure different spatial frequencies.

Result: High correlation(r=0.5~0.6) was found between CSFs obtained with two methods and both in normal and low vision subjects. The CSF curves were found very similar in shape between two methods. Spatial frequency and character size was matched that frequency being inverse of 5 times character size.

Conclusion: Time consuming and costly CSF measurement with sine wave targets would be replacable by quicker and less expensive character- based CSF measurement. And character-based CSF would allow us to predict reading performance of patients with low vision.

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