Chen Spencer C, Hallum Luke E, Lovell Nigel H, Suaning Gregg J
Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
IEEE Trans Neural Syst Rehabil Eng. 2005 Sep;13(3):249-55. doi: 10.1109/TNSRE.2005.851771.
Acceptance of prosthetic vision will be heavily dependent on the ability of recipients to form useful information from such vision. Training strategies to accelerate learning and maximize visual comprehension would need to be designed in the light of the factors affecting human learning under prosthetic vision. Some of these potential factors were examined in a visual acuity study using the Landolt C optotype under virtual-reality simulation of prosthetic vision. Fifteen normally sighted subjects were tested for 10-20 sessions. Potential learning factors were tested at p < 0.05 with regression models. Learning was most evident across-sessions, though 17% of sessions did express significant within-session trends. Learning was highly concentrated toward a critical range of optotype sizes, and subjects were less capable in identifying the closed optotype (a Landolt C with no gap, forming a closed annulus). Training for implant recipients should target these critical sizes and the closed optotype to extend the limit of visual comprehension. Although there was no evidence that image processing affected overall learning, subjects showed varying personal preferences.
对假体视觉的接受程度将在很大程度上取决于接受者从这种视觉中形成有用信息的能力。鉴于影响假体视觉下人类学习的因素，需要设计加速学习并最大化视觉理解的训练策略。在一项使用Landolt C视标的视力研究中，在虚拟现实模拟的假体视觉下对其中一些潜在因素进行了研究。15名视力正常的受试者接受了10至20次测试。使用回归模型在p < 0.05的水平上测试潜在的学习因素。学习在各次测试中最为明显，不过17%的测试确实表现出显著的单次测试内趋势。学习高度集中在视标大小的关键范围内，并且受试者识别闭合视标（无间隙的Landolt C，形成闭合环）的能力较差。对植入接受者的训练应针对这些关键大小和闭合视标，以扩展视觉理解的极限。虽然没有证据表明图像处理会影响整体学习，但受试者表现出不同的个人偏好。
