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Cluster Touch: Improving Touch Accuracy on Smartphones for People with Motor and Situational Impairments

Published:02 May 2019Publication History

ABSTRACT

We present Cluster Touch, a combined user-independent and user-specific touch offset model that improves the accuracy of touch input on smartphones for people with motor impairments, and for people experiencing situational impairments while walking. Cluster Touch combines touch examples from multiple users to create a shared user-independent touch model, which is then updated with touch examples provided by an individual user to make it user-specific. Owing to this combination, Cluster Touch allows people to quickly improve the accuracy of their smartphones by providing only 20 touch examples. In a user study with 12 people with motor impairments and 12 people without motor impairments, but who were walking, Cluster Touch improved touch accuracy by 14.65% for the former group and 6.81% for the latter group over the native touch sensor. Furthermore, in an offline analysis of existing mobile interfaces, Cluster Touch improved touch accuracy by 8.21% and 4.84% over the native touch sensor for the two user groups, respectively.

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    • Published in

      cover image ACM Conferences
      CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
      May 2019
      9077 pages
      ISBN:9781450359702
      DOI:10.1145/3290605

      Copyright © 2019 ACM

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      Publication History

      • Published: 2 May 2019

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      CHI '19 Paper Acceptance Rate703of2,958submissions,24%Overall Acceptance Rate6,199of26,314submissions,24%

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