Purchase this article with an account.
Ying Zhao, Yanyu Lu, Chuanqing Zhou, Yao Chen, Qiushi Ren, Xinyu Chai; Chinese Character Recognition Using Simulated Phosphene Maps. Invest. Ophthalmol. Vis. Sci. 2011;52(6):3404-3412. doi: 10.1167/iovs.09-4234.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
A visual prosthetic device may produce phosphene maps in which individual phosphene characteristics can be altered. This study was an investigation of the ability of normally sighted subjects to recognize Chinese characters (CCs) after altering simulated phosphene maps.
Thirty volunteers with normal or corrected visual acuity of 20/20 were recruited. CC recognition accuracy and response time were investigated while one parameter was changed (distortion, pixel dropout percentage, pixel size variability, or pixel gray level) or different combinations of three parameters were used. Five hundred CCs consisting of 1 to 16 strokes were used for the character sets.
CC recognition accuracy and response times respectively decreased and increased when distortion, dropout, and pixel size variability increased. Gray levels did not significantly affect the results, except when eight levels were used. To maintain an 80% accuracy rate, there should be a distortion index (k) of no more than 0.2 (irregularity), a pixel dropout of 20%, and a pixel size range of 1 to 16 mm (7–112 min arc). Only a combination of a k = 0.1 distortion index, a dropout of 10%, and a pixel size range of 1.33 to 12 mm (9.3–84 min arc) achieved a goal of ≥80% accuracy.
Distortion, dropout percentage, and pixel size variability have a significant impact on pixelated CC recognition. Although at present the visual ability of prosthesis users is limited, it should be possible to extend this to CC recognition and reading in the future. The results will help visual prosthesis researchers determine the effects of altering phosphene maps and improve outcomes for patients.
This PDF is available to Subscribers Only