Department of Biomedical Engineering, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Invest Ophthalmol Vis Sci. 2011 May 1;52(6):3404-12. doi: 10.1167/iovs.09-4234.
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.
视觉假体设备可以产生单个闪光特征可以改变的闪光图谱。本研究旨在调查正常视力受试者在改变模拟闪光图谱后识别汉字(CC)的能力。
招募了 30 名视力正常或矫正视力为 20/20 的志愿者。在改变一个参数(变形、像素缺失百分比、像素大小变化或像素灰度级)或使用三个参数的不同组合时,调查 CC 识别准确性和响应时间。使用了由 1 到 16 个笔画组成的 500 个 CC 字符集。
当变形、丢失和像素大小变化增加时,CC 识别准确性和响应时间分别降低和增加。灰度级除了使用 8 个级别外,没有显著影响结果。为了保持 80%的准确率,应该有一个不超过 0.2 的失真指数(k)(不规则),像素丢失率为 20%,像素大小范围为 1 到 16 毫米(7-112 分弧)。只有 k=0.1 的失真指数、10%的丢失率和 1.33 到 12 毫米(9.3-84 分弧)的像素大小范围的组合才能达到≥80%的准确率。
变形、丢失百分比和像素大小变化对像素化 CC 识别有显著影响。尽管目前假体使用者的视觉能力有限,但将来应该有可能扩展到 CC 识别和阅读。结果将帮助视觉假体研究人员确定改变闪光图谱的影响,并改善患者的结果。