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. 2020 Dec 18;9(13):32.
doi: 10.1167/tvst.9.13.32. eCollection 2020 Dec.

Testing Vision Is Not Testing For Vision

Affiliations

Testing Vision Is Not Testing For Vision

Eli Peli. Transl Vis Sci Technol. .

Abstract

Visual prostheses aim to restore, at least to some extent, vision that leads to the type of perception available for sighted patients. Their effectiveness is almost always evaluated using clinical tests of vision. Clinical vision tests are designed to measure the limits of parameters of a functioning visual system. I argue here that these tests are rarely suited to determine the ability of prosthetic devices and other therapies to restore vision. This paper describes and explains many limitations of these evaluations. Prosthetic vision testing often makes use of multiple-alternative forced-choice (MAFC) procedures. Although these paradigms are suitable for many studies, they are frequently problematic in vision restoration evaluation. Two main types of problems are identified: (1) where nuisance variables provide spurious cues that can be learned in repeated training, which is common in prosthetic vision, and thus defeat the purpose of the test; and (2) even though a test is properly designed and performed, it may not actually measure what the researchers believe, and thus the interpretation of results is wrong. Examples for both types of problems are presented. Additional problems arise from confounding factors in the administration of tests are pointed as limitations of current device evaluation. For example, head tracing of magnified objects enlarged to compensate for the system's low resolution, in distinction from the scanning head (camera) movements with which users of prosthetic devices expand the limited field of view. Because of these problems, the ability to perform satisfactorily on the clinical tests is necessary but insufficient to prove vision restoration, therefore, additional tests are needed. I propose some directions to pursue in such testing.

Translational relevance: Numerous prosthetic devices are being developed and introduced to the market. Proving the utility of these devices is crucial for regulatory and even for post market acceptance, which so far has largely failed, in my opinion. Potential reasons for the failures despite success in regulatory testing and directions for designing improved testing are provided. It is hoped that improved testing will guide improved designs of future prosthetic systems and other vision restoration approaches.

Keywords: gene therapy; optogenetic; prosthetic vision; sensory substitution; spatial perception; stem cell; vision restoration; visual perception.

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Conflict of interest statement

Disclosure: E. Peli, has two patents and a patent application on image processing for visual prostheses, all assigned to the Schepens Eye Research Institute

Figures

Figure 1.
Figure 1.
Illustrations of the low-resolution visual representation of word images used in the Han et al. study. (a) Three of the 10 words showing the crude outline in blue dots. Note the difference and possible cues in the position of ascending and descending letters (b). The actual image of the word “dog” as it was presented on the computer screen in the study. Adapted from Han et al.
Figure 2.
Figure 2.
Improvement in correct recognition of the word images with training. A dramatic improvement in the 10 trained words compared to the 50 untrained words is apparent. The improvement during training is rapid and reaches about 100% quickly. The performance in the post-training test is slightly reduced due to the mix with the 50 untrained words in that test. Adapted from Han et al. ****: P < 0.0001, *****: P < 0.00001.

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