Abstract
The previous chapter proposes a user model to personalize existing interfaces. However, we can think beyond personalization to facilitate human–machine interaction. The survey in Chap. 1 pointed out that a few elderly users found it difficult to operate a mouse or found the buttons on a TV remote too small to touch. This chapter proposes new interaction modalities involving eye-gaze and head movement trackers .
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Adjouadi, M., Sesin, A., Ayala, M., & Cabrerizo, M. (2004). Remote eye gaze tracking system as a computer interface for persons with severe motor disability. ICCHP 2004, LNCS, 3118, 761–769.
Allison, R. S., Eizenman, M., & Cheung, B. S. K. (1996). Combined head and eye tracking system for dynamic testing of the vestibular system. IEEE Transaction on Biomedical Engineering, 43(11).
Asano, T., Sharlin, E., Kitamura, Y., Takashima, K., & Kishino, F. (2005). Predictive interaction using the delphian desktop. Proceedings of the 186th annual ACM smposium on User Interface Software and Technology (UIST 2005) (pp. 133–141), New York.
Ashdown, M., Oka, K., & Sato, Y. (2005). Combining head tracking and mouse input for a GUI on multiple monitors. CHI Late breaking Result.
Bates, R. (1999). Multimodal eye-based interaction for zoomed target selection on a standard graphical user interface. INTERACT.
Biswas, P., & Robinson, P. (2009). Modelling perception using image processing algorithms. 23rd British computer society conference on Human-Computer Interaction (HCI 2009)
Biswas, P., & Langdon, P. (June 2011). A new input system for disabled users involving eye gaze tracker and scanning interface. Journal of Assistive Technologies, 5(2). ISSN:1754-9450
Biswas, P., & Langdon, P. (2012). Developing multimodal adaptation algorithm for mobility impaired users by evaluating their hand strength. International Journal of Human-Computer Interaction, 28(9). (Taylor & Francis, Print ISSN:1044-7318).
CameraMouse. (2013). http://www.cameramouse.com. Accessed 22 Sep 2013.
Dixon, M., Fogarty, J., & Wobbrock, J. (2012). A general-purpose target-aware pointing enhancement using pixel-level analysis of graphical interfaces. Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems (CHI 2012) (pp. 3167–3176). New York: ACM.
Donegan, M., et al. (2009). Understanding users and their needs. Universal Access in the Information Society, 8, 259–275.
Dostal, J., Kristensson, P. O., & Quigley, A. (2013). Subtle gaze-dependent techniques for visualising display changes in multi-display environments. ACM international conference of Intelligent User Interfaces (IUI 2013).
Duchowski, A. T. (2007). Eye tracking methodology. New York: Springer.
Emotiv Epoch (2013). http://www.emotiv.com/. Accessed 31 Aug 2013.
Evans, A. C., & Wobbrock, J. O. (5–10 May 2012). Taming wild behavior: The input observer for obtaining text entry and mouse pointing measures from everyday computer use. Proceedings of the ACM conference on Human Factors in Computing Systems (CHI ’12). Austin, Texas (pp. 1947–1956). New York: ACM.
Facelab Eye Tracker (2013). http://www.seeingmachines.com/product/facelab/. Accessed 29 April 2013.
Fejtova, M., et al. (2009). Hands-free interaction with a computer and other technologies. Universal Access in the Information Society, 8.
Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47, 381–391.
Fu, Y., & Huang, T. S. (2007). hMouse: Head tracking driven virtual computer mouse. IEEE workshop on applications of computer vision.
Godsill, S., & Vermaak, J. (2004). Models and algorithms for tracking using variable dimension particle filters. International conference on acoustics, speech and signal processing.
Huey, E. (1908). The psychology and pedagogy of reading. Cambridge: MIT Press.
Hwang, F., Hollinworth, N., & Williams, N. (2013). ACM Transactions on Accessible Computing (TACCESS) 5(1).
Hwang, F., Keates, S., Langdon, P., & Clarkson, P. J. (2005). A submovement analysis of cursor trajectories. Behaviour and Information Technology, 24(3), 205–217.
Jacob, R. (1993). Eye movement-based human-computer interaction techniques: Toward non-command interfaces. Advances in Human-Computer Interaction.
Jagacinski, R. J., & Monk, D. L. (1985). Fitts’ Law in two dimensions with hand and head movements. Journal of Motor Behaviour, 17(1), 77–95.
Keates, S., Hwang, F., Langdon, P., Clarkson, P. J., & Robinson, P. (2002). Cursor measures for motion-impaired computer users. Proceedings of the fifth international ACM conference on Assistive Technologies—ASSETS (pp. 135–142). New York
Lane, D. M., Peres, S. C., Sándor, A., & Napier, H. A. (2005). A process for anticipating and executing icon selection in graphical user interfaces. International Journal of Human Computer Interaction, 19(2), 243–254.
Langdon, P. M., Godsill, S., & Clarkson, P. J. (2006). Statistical estimation of user’s interactions from motion impaired cursor use data. 6th International Conference on Disability, Virtual Reality and Associated Technologies (ICDVRAT 2006), Esbjerg.
Lank, E., Cheng, Y. N., & Ruiz, J. (2007). Endpoint prediction using motion kinematics. Proceedings of the SIGCHI conference on Human factors in computing systems (CHI ’07) (pp. 637–646). New York.
Lee, D., Kwon, S., & Chung, M. K. (2012). Effects of user age and target-expansion methods on target-acquisition tasks using a mouse. Applied Ergonomics, 43(1), 166–175.
Li, X. R., & Jilkov, V. P. (2003). Survey of maneuvering target tracking. Part I. Dynamic models. IEEE Transactions on Aerospace and Electronic Systems, 39(4), 1333–1364.
MacKenzie, I. S., Sellen, A., & Buxton, W. (1991). A comparison of input devices in elemental pointing and dragging tasks. Proceedings of the CHI ’91 conference on Human factors in computing systems (pp. 161–166). New York: ACM.
Majaranta, P., & Raiha, K. (2002) Twenty years of eye typing: Systems and design issues. Eye tracking research & application.
McGuffin, M. J., & Balakrishnan, R. (2005). Fitts’ law and expanding targets: Experimental studies and designs for user interfaces. ACM Transactions Computer-Human Interaction, 12(4), 388–422.
Miniotas, D. (2001). Application of Fitts’ Law to eye gaze interaction. Proceedings of the ACM SIGCHI conference on Human factors in computing systems (CHI) (pp. 339–340).
Murata, A. (1998). Improvement of pointing time by predicting targets in pointing with a PC mouse. International Journal of Human-Computer Interaction, 10(1), 23–32.
Oirschot, H., & Houtsma, A. J. M. (2001) Cursor trajectory analysis. In S. Brewster & R. Murray-Smith (Eds.), Haptic Human-Computer Interaction (LNCS Vol. 2058, pp. 127–134). Springer: Berlin.
Ruiz, J., & Lank, E. (2010). Speeding pointing in tiled widgets: Understanding the effects of target expansion and misprediction. Proceedings of the 15th international conference on Intelligent User Interfaces (IUI’10) (pp. 229–238). New York: ACM.
Salomon, D. (Aug. 2005). Curves and surfaces for computer graphics (ISBN:0-387-24196-24195). New York: Springer.
Tobii X120 Eye Tracker. (2013). http://www.tobii.com/en/eye-tracking-research/global/products/hardware/tobii-x60x120-eye-tracker/. Accessed 31 Aug 2013.
Vertegaal, R. (2008). A Fitts’ Law comparison of eye tracking and manual input in the selection of visual targets. Proceedings of the international conference of multimodal interaction (pp. 241–248).
Ward, D. (2010). Dasher with an eye-tracker. http://www.inference.phy.cam.ac.uk/djw30/dasher/eye.html. Accessed 19 Aug 2010.
Ware, C., & Mikaelian, H. M. (1987). An evaluation of an eye tracker as a device for computer input. Proceedings of the ACM SIGCHI conference on Human factors in computing systems (CHI) (pp. 183–187).
Wobbrock, J. O., Fogarty, J., Liu, S., Kimuro, S., & Harada, S. (2009). The angle mouse: Target-agnostic dynamic gain adjustment based on angular deviation. Proceedings of the 27th international conference on Human factors in computing systems (CHI ’09) (pp. 1401–1410). New York.
Woodworth, R. S. (1899). The accuracy of voluntary movement. Psychological Review, 3, 1–119.
Zandera, T. O., Gaertnera, M., Kothea, C., & Vilimek, R. (2010). Combining eye gaze input with a brain-computer interface for touchless human-computer interaction. International Journal of Human-Computer Interaction, 27(1).
Zhai, S., Morimoto, C., & Ihde, S. (1999). Manual and Gaze Input Cascaded (MAGIC) Pointing. ACM SIGCHI conference on Human factors in computing system (CHI).
Zhang, Y., Bulling, A., & Gellersen, H. (2013). SideWays: A gaze interface for spontaneous interaction with situated displays. CHI 2013.
Ziebart, B., Dey, A., & Bagnell, J. A. (2012). Probabilistic pointing target prediction via inverse optimal control. Proceedings of the 2012 ACM international conference on Intelligent User Interfaces (IUI ’12) (pp. 1–10). New York.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Biswas, P. (2014). User Interaction. In: Inclusive Human Machine Interaction for India. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-06500-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-06500-7_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06165-8
Online ISBN: 978-3-319-06500-7
eBook Packages: Computer ScienceComputer Science (R0)