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ADAMAAS: Towards Smart Glasses for Mobile and Personalized Action Assistance

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Published:29 June 2016Publication History

ABSTRACT

In this paper, we describe the assistive system ADAMAAS (Adaptive and Mobile Action Assistance) introducing a new advanced smartglasses technology. The aim of ADAMAAS is to move from stationary status diagnosis systems to a mobile and adaptive action support and monitoring system, which is able to dynamically react in a context-sensitive way to human error (slips and mistakes) and to provide individualized feedback on a transparent virtual plane superimposed on user's field of view. For this purpose ADAMAAS uses advanced technologies like augmented reality (AR), eye tracking, object recognition, and systematic analysis of users' mental representations in long-term memory. Preliminary user tests with disabled participants at an early prototype stage revealed no substantial physical restrictions in the execution of their activities, positive feedback regarding the assistive hints, and that participants could imagine wearing the glasses for long periods of time.

References

  1. Pfeiffer, T. (2013). Gaze-based assistive technologies. In G. Kouroupetroglou (Ed.), Assistive Technologies and Computer Access for Motor Disabilities (pp. 90--109). Hershey:IGI Global.Google ScholarGoogle Scholar
  2. Koesling, H., Zoellner, M., Sichelschmidt, M., & Ritter, H. (2009). With a flick of the eye: Assessing gaze-controlled human-computer interaction. In: H. Ritter, G. Sagerer, R. Dillmann, and M. Buss (Eds.), Cognitive Systems Monographs, Human Centered Robot Systems: Cognition, Interaction, Technology (pp. 83--92). Berlin: Springer VerlagGoogle ScholarGoogle Scholar
  3. Jacob, R.J.K. (1993). What you look at is what you get. Computer, 26(7), pp. 65--66. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Dybdal, M.L., San Agustin, J., & Hansen J.P. (2012). Gaze input for mobile devices by dwell and gestures. In: Proceedings of the symposium on eye tracking research and applications, ETRA 12. ACM, New York, pp 225--228. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Losing, V., Rottkamp, L., Zeunert, M., & Pfeiffer, T. (2014). Guiding Visual Search Tasks Using Gaze-Contingent Auditory Feedback. UbiComp'14 Adjunct: The 2014 ACM Conference on Ubiquitous Computing Adjunct Publication, pp. 1093--1102. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Renner, P. and Pfeiffer, T. (2015). Online Visual Attention Monitoring for Mobile Assistive Systems. In: Pfeiffer T, Essig K, (Eds.), SAGA 2015: 2nd International Workshop on Solutions for Automatic Gaze Data Analysis (pp. 14--15). eCollections Bielefeld University 2015.Google ScholarGoogle Scholar
  7. Holmqvist, K. et al. (2011). Eye tracking -- A comprehensive guide to methods and measures. New York: Oxford University Press.Google ScholarGoogle Scholar
  8. Just, M.A. and Carpenter, P.A. (1987). The Psychology of Reading and Language. Newton: Allyn and Bacon.Google ScholarGoogle Scholar
  9. Reinert, G. (1993). Augenbewegungen bei geistig behinderten Kindern. Lehrstuhlbericht. Arbeitsgruppe für Umwelt und Kognitionspsychologie, Ruhr-Universität Bochum, Germany.Google ScholarGoogle Scholar
  10. Majaranta, P. et al. 2012. Gaze Interaction and Applications of Eye Tracking -- Advances in Assistive Technologies. Hershey: IGI Global. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Schack, T. (2012). Measuring mental representations. In Measurement in sport and exercise psychology (pp. 203--214). Champaign, IL: Human Kinetics.Google ScholarGoogle Scholar
  12. Ueckermann, A. et al. (2014). Real --Time Hierarchical Scene Segmentation and Classification. 14th IEEE-RAS International Conference on Humanoid Robots (Humanoids), November 18-20, 2014, Madrid, Spain.Google ScholarGoogle Scholar
  13. Schröder, M., Maycock, J., Ritter, H., & Botsch, M. (2014). Real-Time Hand Tracking using Synergistic Inverse Kinematics. IEEE International Conference on Robotics and Automation (ICRA), pp. 5447--5454.Google ScholarGoogle ScholarCross RefCross Ref
  14. Fischer, H., Strenge, B., & Nebe, K. (2013). Towards a holistic tool for the selection and validation of usability method sets supporting human-centered design. In Design, User Experience, and Usability. Design Philosophy, Methods, and Tools (pp. 252--261). Springer Berlin Heidelberg. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Sinha, R. (2003). Persona development for information-rich domains. In CHI'03 extended abstracts on Human factors in computing systems (pp. 830--831). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Tu, N., Dong, X., Rau, P., & Zhang, T. (2010). Using cluster analysis in persona development. In International Conference on Supply Chain Management and Information Systems.Google ScholarGoogle Scholar
  17. Schwaber, K., & Sutherland, J. (2013). The Scrum Guide-- The Definitive Guide to Scrum: The Rules of the Game. URL: http://www.scrumguides.orgGoogle ScholarGoogle Scholar
  18. Beck, K. (2000). Extreme programming explained: embrace change. Addison-Wesley. Google ScholarGoogle ScholarDigital LibraryDigital Library
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    • Published in

      cover image ACM Other conferences
      PETRA '16: Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments
      June 2016
      455 pages
      ISBN:9781450343374
      DOI:10.1145/2910674

      Copyright © 2016 ACM

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      Publication History

      • Published: 29 June 2016

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