• DocumentCode
    1161775
  • Title

    Learning prosthetic vision: a virtual-reality study

  • Author

    Chen, Spencer C. ; Hallum, Luke E. ; Lovell, Nigel H. ; Suaning, Gregg J.

  • Author_Institution
    Graduate Sch. of Biomed. Eng., Univ. of New South Wales, Sydney, NSW, Australia
  • Volume
    13
  • Issue
    3
  • fYear
    2005
  • Firstpage
    249
  • Lastpage
    255
  • Abstract
    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.
  • Keywords
    neurophysiology; prosthetics; regression analysis; virtual reality; visual perception; Landolt C optotype; human learning; image processing; prosthetic vision; regression models; virtual reality; visual acuity; visual comprehension; Acceleration; Auditory system; Australia; Biomedical engineering; Clinical trials; Cochlear implants; Humans; Neural prosthesis; Prosthetics; Testing; Learning; prosthetic vision; virtual-reality; vision prosthesis; Adolescent; Adult; Artificial Intelligence; Computer Graphics; Data Display; Female; Humans; Learning; Male; Prostheses and Implants; Prosthesis Fitting; User-Computer Interface; Vision Disorders; Vision Tests; Visual Acuity; Visual Perception;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2005.851771
  • Filename
    1506811