Filteryedping: Design Challenges and User Performance of Dwell-Free Eye Typing

Author:

Pedrosa Diogo1,Pimentel Maria Da Graça1,Wright Amy2,Truong Khai N.3

Affiliation:

1. ICMC--University of Sao Paulo, SP, Brazil, CEP

2. Carolinas Neuromuscular/ALS-MDA Center, Charlotte, NC, USA

3. University of North Carolina at Charlotte, Charlotte, NC, USA

Abstract

The ability to use the movements of the eyes to write is extremely important for individuals with a severe motor disability. With eye typing, a virtual keyboard is shown on the screen and the user enters text by gazing at the intended keys one at a time. With dwell-based eye typing, a key is selected by continuously gazing at it for a specific amount of time. However, this approach has two possible drawbacks: unwanted selections and slow typing rates. In this study, we propose a dwell-free eye typing technique that filters out unintentionally selected letters from the sequence of letters looked at by the user. It ranks possible words based on their length and frequency of use and suggests them to the user. We evaluated Filteryedping with a series of experiments. First, we recruited participants without disabilities to compare it with another potential dwell-free technique and with a dwell-based eye typing interface. The results indicate it is a fast technique that allows an average of 15.95 words per minute after 100min of typing. Then, we improved the technique through iterative design and evaluation with individuals who have severe motor disabilities. This phase helped to identify and create parameters that allow the technique to be adapted to different users.

Funder

São Paulo Research Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,Human-Computer Interaction

Reference35 articles.

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3. The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function

4. Design and evaluation of a dwell-free eye typing technique

5. Mark Davies. 2008. The corpus of contemporary American English (COCA): 450 million words 1990--2012. Retrieved from http://www.americancorpus.org. Mark Davies. 2008. The corpus of contemporary American English (COCA): 450 million words 1990--2012. Retrieved from http://www.americancorpus.org.

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