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Investigation of the recognition of different font sizes on human-machine interface and physiological characteristics for aged people

  • Shengwen Luo
  • , Li Ding
  • , Linghua Ran
  • , Yan Li*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the growing population of the elderly people, designers of the human-machine interface must consider their psychophysiological characteristics. Three groups of subjects with a mean age of 21.0, 38.5 and 61.5 years, participated in the experiments. First they were examined by the perimeter. Then their near vision were measured by the Landolt ring test. Finally a Chinese character choosing task was done. The senile group had a marked decrease of light sensitivity and also a decline of near vision. For the 9-point font, there was no significant difference among three groups. However, for the 6-point font, the senile group reacted slowly. In the future, for the sake of the aged people, it would be of great importance to work out the critical and optimal font sizes under different light conditions. To obtain this goal, more experiments should be done and more subjects should be involved.

Original languageEnglish
Title of host publicationAdvances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE International Conference on Neuroergonomics and Cognitive Engineering, 2016
EditorsKelly S. Hale, Kay M. Stanney
PublisherSpringer Verlag
Pages17-26
Number of pages10
ISBN (Print)9783319416908
DOIs
StatePublished - 2017
EventInternational Conference on Neuroergonomics and Cognitive Engineering, 2016 - Walt Disney World, United States
Duration: 27 Jul 201631 Jul 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume488
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Neuroergonomics and Cognitive Engineering, 2016
Country/TerritoryUnited States
CityWalt Disney World
Period27/07/1631/07/16

Keywords

  • Font sizes recognition
  • Human-Machine interface design
  • Physiological characteristics

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