优化汉字显示设备可改善模拟不规则光幻视图的识别与阅读能力

School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

PURPOSE. A visual prosthesis may elicit an irregular phosphene map relative to a regular electrode array. This study used simulated irregular phosphene maps as a way of optimizing the display methods of Chinese characters (CCs) to improve recognition and reading performance. METHODS. Twenty subjects with normal or corrected sight participated in two experiments (9 females, 11 males, 20-30 years of age). Experiment 1: two character display methods were proposed: selecting phosphenes covered by character strokes on a simulated phosphene array (projection method) and finding the phosphene closest to the expected location in some range of an irregular phosphene array as a substitute (nearest neighbor search [NNS] method). The recognition accuracy of CCs was investigated using six levels for the coverage ratio of stroke and phosphene area and for search range, respectively, for two methods, for several irregularity levels. Experiment 2: reading accuracy (RA) and reading efficiency (RE) were measured using the regular array correspondence and NNS methods. RESULTS. Experiment 1: projection and NNS methods were significantly affected by coverage ratio or search range. NNS significantly improved CC recognition accuracy to the highest at 81.3± 2.7% and 59.1±5.2%, respectively, for different irregularity levels, compared with the projection method. Experiment 2: RA and RE significantly decreased as the distortion level increased; NNS significantly improved RA (from approximately 40% to >80%) and RE (from approximately 13 char/min to >40 char/min) when reading more irregular paragraphs. CONCLUSIONS. The performance of CC recognition and paragraph reading when using an irregular phosphene array can be improved through optimizing the display method. © 2013 The Association for Research in Vision and Ophthalmology, Inc.

Lu, Y.; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; email:xychai@sjtu.edu.cn