Visual Field Loss Compensation for Homonymous Hemianopia Patients Using Edge Indicator

Keisuke Ichinose, Issei Fujishiro, Kenji Kashiwagi, Xiaoyang Mao, Xi Zhao, Masahiro Toyoura, Kentaro Go

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Homonymous hemianopia (HH) is one kind of visual field defect that the right or left half of the visual fields of both eyes are missing. HH is caused by damage to the neural pathways of the brain and a complete recovery is usually difficult. This study proposes a new information compensation method for HH patients using optical-see-through head mounted display. To avoid causing the occlusion, the proposed technique uses indicators placed at the boundary between the lost and remaining sides of visual field to notify patients about the changes in the lost side. Experiment involving simulated HH participants was conducted to verify the effectiveness of the proposed method and compare with the existing method using overlaid overview window. Objective and subjective evaluation results show that the proposed method can partially alleviate the occlusion problem of overlaid overview window approach and has lower physical and mental demand.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Cyberworlds, CW 2020
EditorsAlexei Sourin, Christophe Charier, Christophe Rosenberger, Olga Sourina
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages79-85
Number of pages7
ISBN (Electronic)9781728164977
DOIs
Publication statusPublished - 2020 Sept
Event19th International Conference on Cyberworlds, CW 2020 - Virtual, Caen, France
Duration: 2020 Sept 292020 Oct 1

Publication series

NameProceedings - 2020 International Conference on Cyberworlds, CW 2020

Conference

Conference19th International Conference on Cyberworlds, CW 2020
Country/TerritoryFrance
CityVirtual, Caen
Period20/9/2920/10/1

Keywords

  • edge indicator
  • homonymous hemianopia
  • out-of-visual-field information compensation
  • visual field defect

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Media Technology
  • Modelling and Simulation

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