Advertisement

Multi-switch Scanning Keyboards: A Theoretical Study of Simultaneous Parallel Scans with QWERTY Layout

  • Frode Eika Sandnes
  • Evelyn Eika
  • Fausto Orsi Medola
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10907)

Abstract

Scanning keyboards can be useful aids for individuals with reduced motor function. However, scanning input techniques are known for being very slow to use because they require waiting for the right cell to be highlighted during each character input cycle. This study explores the idea of parallel scanning keyboards controlled with multiple switches and their theoretical effects on performance. The designs explored assume that the keyboard layouts are familiar to users and that the mapping between the switches and the keyboards are natural and direct. The results show that the theoretical performance increases linearly with the number of switches used. Future work should perform user tests with parallel scans to assess the practicality of this approach.

Keywords

Scanning keyboards Text entry Joystick Parallel scans Reduced motor function 

References

  1. 1.
    Polacek, O., Sporka, A.J., Slavik, P.: Text input for motor-impaired people. Univers. Access Inf. Soc. 16, 51–72 (2017)CrossRefGoogle Scholar
  2. 2.
    Abascal, J., Gardeazabal, L., Garay, N.: Optimisation of the selection set features for scanning text input. In: Miesenberger, K., Klaus, J., Zagler, W.L., Burger, D. (eds.) ICCHP 2004. LNCS, vol. 3118, pp. 788–795. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-27817-7_117CrossRefGoogle Scholar
  3. 3.
    Higger, M., Moghadamfalahi, M., Quivira, F., Erdogmus, D.: Fast switch scanning keyboards: minimal expected query decision trees. arXiv preprint arXiv:1606.02552 (2016)
  4. 4.
    Zhang, X.C., Fang, K., Francis, G.: Optimization of switch keyboards. In: Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility. ACM (2013)Google Scholar
  5. 5.
    Jones, P.E.: Virtual keyboard with scanning and augmented by prediction. In: Proceedings of the 2nd European Conference on Disability, Virtual Reality and Associated Technologies, pp. 45–51 (1998)Google Scholar
  6. 6.
    Mackenzie, I.S., Felzer, T.: SAK: scanning ambiguous keyboard for efficient one-key text entry. ACM Trans. Comput.-Hum. Interact. (TOCHI) 17, (2010)CrossRefGoogle Scholar
  7. 7.
    Zhang, X., Fang, K., Francis, G.: How to optimize switch virtual keyboards to trade off speed and accuracy. Cogn. Res.: Princ. Implic. 1, 6 (2016)CrossRefGoogle Scholar
  8. 8.
    Simpson, R.C., Mankowski, R., Koester, H.H.: Modeling one-switch row-column scanning with errors and error correction methods. Open Rehabil. J. 4, 1–12 (2011)CrossRefGoogle Scholar
  9. 9.
    Francis, G., Johnson, E.: Speed–accuracy tradeoffs in specialized keyboards. Int. J. Hum.-Comput. Stud. 69, 526–538 (2011)CrossRefGoogle Scholar
  10. 10.
    Levine, S., Gauger, J., Bowers, L., Khan, K.: A comparison of mouthstick and morse code text inputs. Augment. Altern. Commun. 2, 51–55 (1986)CrossRefGoogle Scholar
  11. 11.
    Sandnes, F.E., Medola, F.O.: Exploring Russian tap-code text entry adaptions for users with reduced target hitting accuracy. In: Proceedings of the 7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion, pp. 33–38. ACM (2016)Google Scholar
  12. 12.
    Gong, J., Haggerty, B., Tarasewich, P.: An enhanced multitap text entry method with predictive next-letter highlighting. In: CHI 2005 Extended Abstracts on Human Factors in Computing Systems, pp. 1399–1402. ACM (2005)Google Scholar
  13. 13.
    Sandnes, F.E.: Can spatial mnemonics accelerate the learning of text input chords? In: Proceedings of the Working Conference on Advanced Visual Interfaces, pp. 245–249. ACM (2006)Google Scholar
  14. 14.
    Sandnes, F.E.: Human performance characteristics of three-finger chord sequences. Procedia Manuf. 3, 4228–4235 (2015)CrossRefGoogle Scholar
  15. 15.
    Sandnes, F.E., Huang, Y.P.: Chording with spatial mnemonics: automatic error correction for eyes-free text entry. J. Inf. Sci. Eng. 22, 1015–1031 (2006)Google Scholar
  16. 16.
    Sandnes, F.E., Huang, Y.P.: Chord level error correction for portable Braille devices. Electron. Lett. 42, 82–83 (2006)CrossRefGoogle Scholar
  17. 17.
    Sandnes, F.E., Thorkildssen, H.W., Arvei, A., Buverad, J.O.: Techniques for fast and easy mobile text-entry with three-keys. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences. IEEE (2004)Google Scholar
  18. 18.
    Sandnes, F.E., Jian, H.-L.: Pair-wise variability index: evaluating the cognitive difficulty of using mobile text entry systems. In: Brewster, S., Dunlop, M. (eds.) Mobile HCI 2004. LNCS, vol. 3160, pp. 347–350. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-28637-0_35CrossRefGoogle Scholar
  19. 19.
    Sandnes, F.E., Tan, T.B., Johansen, A., Sulic, E., Vesterhus, E., Iversen, E.R.: Making touch-based kiosks accessible to blind users through simple gestures. Univers. Access Inf. Soc. 11, 421–431 (2012)CrossRefGoogle Scholar
  20. 20.
    Perlin, K.: Quikwriting: continuous stylus-based text entry. In: Proceedings of the 11th Annual ACM Symposium on User Interface Software and Technology, pp. 215–216. ACM (1998)Google Scholar
  21. 21.
    Darragh, J.J., Witten, I.H., James, M.L.: The reactive keyboard: a predictive typing aid. Computer 23, 41–49 (1990)CrossRefGoogle Scholar
  22. 22.
    Sandnes, F.E.: Reflective text entry: a simple low effort predictive input method based on flexible abbreviations. Procedia Comput. Sci. 67, 105–112 (2015)CrossRefGoogle Scholar
  23. 23.
    Berget, G., Sandnes, F.E.: Do autocomplete functions reduce the impact of dyslexia on information searching behaviour? A case of Google. J. Am. Soc. Inf. Sci. Technol. 67, 2320–2328 (2016)CrossRefGoogle Scholar
  24. 24.
    Berget, G., Sandnes, F.E.: Searching databases without query-building aids: implications for dyslexic users. Inf. Res. 20, n4 (2015)Google Scholar
  25. 25.
    Huang, Y.P., Chang, Y.T., Sandnes, F.E.: Ubiquitous information transfer across different platforms by QR codes. J. Mob. Multimed. 6, 3–13 (2010)Google Scholar
  26. 26.
    Sandnes, F.E., Herstad, J., Stangeland, A.M., Orsi Medola, F.: UbiWheel: a simple context-aware universal control concept for smart home appliances that encourages active living. In: Proceedings of Smartworld 2017, pp. 446–451. IEEE (2017)Google Scholar
  27. 27.
    Bhattacharya, S., Samanta, D., Basu, A.: Performance models for automatic evaluation of virtual scanning keyboards. IEEE Trans. Neural Syst. Rehabil. Eng. 16, 510–519 (2008)CrossRefGoogle Scholar
  28. 28.
    MacKenzie, I.S.: Modeling text input for single-switch scanning. In: Miesenberger, K., Karshmer, A., Penaz, P., Zagler, W. (eds.) ICCHP 2012. LNCS, vol. 7383, pp. 423–430. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-31534-3_63CrossRefGoogle Scholar
  29. 29.
    Sandnes, F.E., Aubert, A.: Bimanual text entry using game controllers: relying on users’ spatial familiarity with QWERTY. Interact. Comput. 19, 140–150 (2007)CrossRefGoogle Scholar
  30. 30.
    Sandnes, F.E.: Effects of common keyboard layouts on physical effort: implications for kiosks and Internet banking. In: Sandnes, F.E., Lunde, M. Tollefsen, M., Hauge, A.M., Øverby, E., Brynn, R. (eds.) Proceedings of Unitech2010: International Conference on Universal Technologies, pp. 91–100. Tapir Academic Publishers (2010)Google Scholar
  31. 31.
    Sandnes, F.E.: Directional bias in scrolling tasks: a study of users’ scrolling behaviour using a mobile text-entry strategy. Behav. Inf. Technol. 27, 387–393 (2008)CrossRefGoogle Scholar
  32. 32.
    Sandnes, F.E., Medola, F.O.: Effects of optimizing the scan-path on scanning keyboards with QWERTY-layout for English text. Stud. Health Technol. Inform. 242, 930–938 (2017)Google Scholar
  33. 33.
    Sandnes, F.E.: Evaluating mobile text entry strategies with finite state automata. In: Proceedings of the 7th International Conference on Human Computer Interaction with Mobile Devices & Services, pp. 115–121. ACM (2005)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Frode Eika Sandnes
    • 1
    • 2
  • Evelyn Eika
    • 1
  • Fausto Orsi Medola
    • 3
  1. 1.Department of Computer Science, Faculty of Technology, Art and DesignOsloMet – Oslo Metropolitan UniversityOsloNorway
  2. 2.Faculty of TechnologyWesterdals Oslo School of Art, Communication and TechnologyOsloNorway
  3. 3.School of Architecture, Arts and CommunicationSão Paulo State University (UNESP)BauruBrazil

Personalised recommendations