QUT ePrints

Mobility assessment using simulated artificial human vision

Dowling, Jason A., Boles, Wageeh W., & Maeder, Anthony J. (2005) Mobility assessment using simulated artificial human vision. In IEEE Computer Vision and Pattern Recognition, 20-26 June , San Diego.

View at publisher

Abstract

Recent research on Artificial Human Vision (AHV, or visual prostheses) has focused on providing visually meaningful information to the blind through electrical stimulation of a visual system component. This paper reports on the use of a programmable PDA-based AHV simulator which can be used by normally sighted participants. Using three different display types, mobility performance on an indoor artificial mobility course was assessed using Percentage of Preferred Walking Speed (PPWS) and mobility errors. A looming obstacle alert display was not found to assist with mobility performance. Mobility performance increased as participants learned to use the simulation effectively. Posture, head movements and gait were affected by use of the simulation.

Impact and interest:

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

375 since deposited on 27 Jun 2007
92 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 8309
Item Type: Conference Paper
DOI: 10.1109/CVPR.2005.494
ISSN: 1063-6919
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Computer-Human Interaction (080602)
Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > NEUROSCIENCES (110900) > Sensory Systems (110906)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2005 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 27 Jun 2007
Last Modified: 29 Feb 2012 23:11

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page