How Interface Adaptation for Physical Impairment Can Help Able Bodied Users in Situational Impairment

  • P. Biswas
  • P. M. Langdon
  • J. Umadikar
  • S. Kittusami
  • S. Prashant
Conference paper
First Online:

Abstract

Systems and services developed for elderly or disabled people often find useful applications for their able-bodied counterparts—a few examples are mobile amplification control, which was originally developed for people with hearing problems but is helpful in noisy environments, audio cassette versions of books originally developed for blind people, standards of subtitling in television for deaf users and so on. In this study, we evaluate how prediction from a user model developed for physically impaired users can work in situational impairment.

Keywords

Font Size Colour Blindness Human Machine Interaction Wrong Selection Screen Layout 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. Biswas P, Langdon PM (2012) Developing multimodal adaptation algorithm for mobility impaired users by evaluating their hand strength. Int J Hum Comput Interact 28(9):576−596Google Scholar
  2. Biswas P, Langdon PM, Robinson P (2012) Designing inclusive interfaces through user modelling and simulation. Int J Hum Comput Interact 28(1):1–33Google Scholar
  3. IUATC (2013) The IUATC consortium. www.iu-atc.com. Accessed 29 Oct 2013
  4. Kane SK, Wobbrock JO, Smith IE (2008) Getting off the treadmill: evaluating walking user interfaces for mobile devices in public spaces. In: Proceedings of the 10th conference on human-computer interaction with mobile devices and services, Amsterdam, The NetherlandsGoogle Scholar
  5. Macik M, Cerny T, Basek J, Slavik P (2013) Platform-aware rich-form generation for adaptive systems through code-inspection. In: Human factors in computing and informatics, Lecture Notes in Computer Science, vol 7946. Springer, Berlin Google Scholar
  6. Rieman J, Young RM (1996) A dual-space model of iteratively deepening exploratory learning. Int J Hum Comput Stud 44:743–775CrossRefGoogle Scholar
  7. Schildbach B, Rukzio E (2010) Investigating selection and reading performance on a mobile phone while walking. In: Proceedings of the 12th conference on human-computer interaction with mobile devices and services, Lisbon, PortugalGoogle Scholar
  8. The SUPPLE Project (2009) SUPPLE: Automatic generation of personalizable user interfaces. www.cs.washington.edu/ai/supple/. Accessed 29 Oct 2013

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • P. Biswas
    • 1
  • P. M. Langdon
    • 1
  • J. Umadikar
    • 2
  • S. Kittusami
    • 2
  • S. Prashant
    • 2
  1. 1.Engineering Design Centre, Department of EngineeringUniversity of CambridgeCambridgeUK
  2. 2.IITM’s Rural Technology and Business IncubatorChennaiIndia

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