Merging Psychophysical and Psychometric Theory to Estimate Global Visual State Measures from Forced-Choices

2013 Joint IMEKO (International Measurement Confederation) TC1-TC7-TC13 Symposium: Measurement Across Physical and Behavioural Sciences

Massof, Robert W.^1 ; Schmidt, Karen M.^2 ; Laby, Daniel M.^3 ; Kirschen, David^4 ; Meadows, David^5

Johns Hopkins University, United States^1

University of Virginia, United States^2

Harvard University, United States^3

University of California Los Angeles, United States^4

University of Florida, United States^5

关键词: Central visual systems;    Decision levels;    Exposure durations;    Psychometric theories;    Psychophysical measures;    Refractive error;    State measurements;    Visual impairment;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/459/1/012027/pdf
DOI  :  10.1088/1742-6596/459/1/012027

来源: IOP

【 摘 要 】

Visual acuity, a forced-choice psychophysical measure of visual spatial resolution, is the sine qua non of clinical visual impairment testing in ophthalmology and optometry patients with visual system disorders ranging from refractive error to retinal, optic nerve, or central visual system pathology. Visual acuity measures are standardized against a norm, but it is well known that visual acuity depends on a variety of stimulus parameters, including contrast and exposure duration. This paper asks if it is possible to estimate a single global visual state measure from visual acuity measures as a function of stimulus parameters that can represent the patient's overall visual health state with a single variable. Psychophysical theory (at the sensory level) and psychometric theory (at the decision level) are merged to identify the conditions that must be satisfied to derive a global visual state measure from parameterised visual acuity measures. A global visual state measurement model is developed and tested with forced-choice visual acuity measures from 116 subjects with no visual impairments and 560 subjects with uncorrected refractive error. The results are in agreement with the expectations of the model.