Learning prosthetic vision: a virtual-reality study.
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.
Chen
Spencer C
SC
Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
Hallum
Luke E
LE
Lovell
Nigel H
NH
Suaning
Gregg J
GJ
D000293:Adolescent; D000328:Adult; D001185:Artificial Intelligence; D003196:Computer Graphics; D003626:Data Display; D005260:Female; D006801:Humans; D007858:Learning / Q000502:physiology*; D008297:Male; D019736:Prostheses and Implants; D017755:Prosthesis Fitting / Q000379:methods*; D014584:User-Computer Interface; D014786:Vision Disorders / Q000503:physiopathology / Q000534:rehabilitation*; D014787:Vision Tests / Q000379:methods; D014792:Visual Acuity / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*