Requirements for Gesture-Controlled Remote Operation to Facilitate Human-Technology Interaction in the Living Environment of Elderly People

  • Susan VorwergEmail author
  • Cornelia Eicher
  • Heinrich Ruser
  • Felix Piela
  • Felix Obée
  • André Kaltenbach
  • Lars Mechold
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11592)


The “SmartPointer” (SP) technology comprises a universal buttonless gesture-controlled handheld remote device with a simple quasi-intuitive operating structure. With this handset, elderly people will be able to control various household devices in their living environment. In order to develop an age-appropriate SP system, the aim of the study was to determine the requirements of elderly people and people with tremor. For this purpose, a mixed-method design, involving several assessments, a guideline-based interview, a task-based investigation and a questionnaire using a gesture catalog, was applied. The whole sample included 20 seniors being 60 years and older. In the process, qualitative requirements were collected on the topics of device use, operating problems, desired devices for gesture control, receiver unit, gestures, feedback and safety. The interview results emphasized the elderly participants’ needs to an easy and intuitive system use. Furthermore, concerns should be prioritized in order to the development of the system. In the quantitative evaluation, the use of various technical devices was analyzed and the frequency of used gestures was determined based the gesture catalog and the task-based investigation. The most frequently used gestures were horizontal, vertical, circular and targeting gestures. In summary, the elderly people were very interested in, and open-minded towards, the SP-system. In a comparison between healthy persons and persons with tremor, the results demonstrated only minimal differences regarding the requirements.


Gesture and eye-gaze-based interaction SmartPointer Gesture control Remote Human-technology interaction Elderly people 


  1. 1.
    Statistisches Bundesamt: 13th Coordinated Population Projection for Germany (2015).!y=2030&l=en&b=1948. Accessed 26 Feb 2019
  2. 2.
    RKI: Health in Germany – the most important developments (2015). Accessed 27 Feb 2019
  3. 3.
    Kremer-Preiß, U.: Aktuelle und zukunftsträchtige Wohnformen für das Alter. In: Wahl, H.-W., Tesch-Römer, C., Ziegelmann, J. (eds.) Angewandte Gerontologie: Interventionen für ein gutes Altern in 100 Schlüsselbegriffen, pp. 554–561. Kohlhammer, Stuttgart (2012)Google Scholar
  4. 4.
    Oswald, F., Wahl, H.-W.: Alte und neue Umwelten des Alterns – Zur Bedeutung von Wohnen und Technologie für Teilhabe in der späten Lebensphase. In: Naegele, G., et al. (eds.) Teilhabe im Alter gestalten – Aktuelle Themen der sozialen Gerontologie, pp. 113–129. Springer VS. Wiesbaden (2016)CrossRefGoogle Scholar
  5. 5.
    Strese, H., Seidel, U., Knape, T., Botthof, A.: Smart Home in Deutschland – Untersuchung im Rahmen der wissenschaftlichen Begleitung zum Programm Next Generation Media (NGM) des Bundesministeriums für Wirtschaft und Technologie (2010). Institut für Innovation und Technik (iit). Accessed 08 Feb 2019
  6. 6.
    Meyer, S.: Technische Unterstützung im Alter - was ist möglich, was ist sinnvoll? Expertise zum Siebten Altenbericht der Bundesregierung (2016). Deutsches Zentrum für Altersfragen. Accessed 07 Feb 2019
  7. 7.
    Statista: Share of Internet users in Germany from 2014 to 2018, by age (2019). Accessed 27 Feb 2019
  8. 8.
    Statista: Anteil der Internetnutzer nach Endgeräten und Altersgruppen in Deutschland im Jahr 2016 (2019). Accessed 12 Feb 2019
  9. 9.
    Frees, B., Koch, W.: ARD/ZDF-Onlinestudie 2018: Zuwachs bei medialer Internetnutzung und Kommunikation. Media Perspektiven 9, 398–413 (2018)Google Scholar
  10. 10.
    Al-Shamayleh, A., Ahmad, R., Abushariah, M., et al.: A systematic literature review on vision based gesture recognition techniques. J. Multimed. Tools Appl. 77(21), 28121–28184 (2018)CrossRefGoogle Scholar
  11. 11.
    Rautaray, S., Agrawal, A.: Vision based hand gesture recognition for human computer interaction: a survey. Artif. Intell. Rev. 43(1), 1–54 (2015)CrossRefGoogle Scholar
  12. 12.
    Bachmann, D., Weichert, F., Rinkenauer, G.: Review of three-dimensional human-computer interaction with focus on the leap motion controller. Sensors 18(7), 2194 (2018)CrossRefGoogle Scholar
  13. 13.
    Liu, H., Wang, L.: Gesture recognition for human-robot collaboration: a review. Int. J. Ind. Ergon. 68, 355–367 (2018)CrossRefGoogle Scholar
  14. 14.
    Schlömer, T., Poppinga, B., Henze, N., Boll, S.: Gesture recognition with a Wii controller. In: Proceedings of the 2nd International Conference on Tangible and Embedded Interaction (TEI 2008), pp. 11–14 (2008)Google Scholar
  15. 15.
    Louis, E.D., Ottman, R.: How Many People in the USA Have Essential Tremor? Deriving a Population Estimate Based on Epidemiological Data. Tremor and Other Hyperkinetic Movements, 4 (2014). Accessed 27 Feb 2019
  16. 16.
    Deuschl, G., Berg, D.: Essenzieller Tremor: State of the Art der Nervenarzt 4(89), 394–399 (2018)CrossRefGoogle Scholar
  17. 17.
    McDowell, I.: Measuring Health - A Guide to Rating Scales and Questionnaires. Oxford University Press, New York (2006)CrossRefGoogle Scholar
  18. 18.
    Fetz, F., Kornexl, E.: Sportmotorische Tests: praktische Anleitung zu sportmotorischen Tests in Schule und Verein. ÖBV, Wien (1993)Google Scholar
  19. 19.
    Bös, K.: Handbuch Motorische Tests - Sportmotorische Tets, Motorische Funktionstests, Fragebögen zur körperlich-sportlichen Aktivität und sportpsychologische Diagnoseverfahren (3. überarbeitete und erweiterte Ausg.). Hogrefe Verlag GmbH & Co. KG., Göttingen (2017)Google Scholar
  20. 20.
    Ruff, R.M., Parker, S.B.: Gender- and age-specific changes in motor speed and eye-hand coordination in adults: normative values for the finger tapping and grooved pegboard tests. Percept. Motor Skills, 76(3_Suppl.), 1219–1230 (1993). Accessed 08 Feb 2019CrossRefGoogle Scholar
  21. 21.
    Chen, W.: Gesture-based applications for elderly people. In: Kurosu, M. (ed.) HCI 2013. LNCS, vol. 8007, pp. 186–195. Springer, Heidelberg (2013). Scholar
  22. 22.
    Kühnel, C., Westermann, T., Hemmert, F., Kratz, S., Müller, A., Möller, S.: I’m home: defining and evaluating a gesture set for smart-home control. Int. J. Hum Comput Stud. 69, 693–704 (2011)CrossRefGoogle Scholar
  23. 23.
    Statista: Share of smartphone users in Germany in 2017, by age group (2019). Accessed 27 Feb 2019
  24. 24.
    Liang, S.-F.M., Lee, Y.-J.B.: Control with hand gestures by older users: a review. In: Zhou, J., Salvendy, G. (eds.) ITAP 2016. LNCS, vol. 9754, pp. 350–359. Springer, Cham (2016). Scholar
  25. 25.
    Bobeth, J., et al.: Tablet, gestures, remote control? Influence of age on performance and user experience with iTV applications. In: Proceedings of 2014 ACM International Conference on Interactive Experiences for TV and Online Video, Newcastle Upon Tyne, United Kingdom, 25–27 June, pp. 139–146 (2014)Google Scholar
  26. 26.
    Gerling, K.M., Dergousoff, K.K., Mandryk, R.L.: Is movement better? Comparing sedentary and motion-based game controls for older adults. In: Proceedings of Graphics Interface 2013, pp. 133–140. Canadian Information Processing Society (2013)Google Scholar
  27. 27.
    Chung, M.K., Kim, D., Na, S., Lee, D.: Usability evaluation of numeric entry tasks on keypad type and age. Int. J. Ind. Ergon. 40(1), 97–105 (2010)CrossRefGoogle Scholar
  28. 28.
    Hwangbo, H., Yoon, S.H., Jin, B.S., Han, Y.S., Ji, Y.G.: A study of pointing performance of elderly users on smartphones. Int. J. Hum.-Comput. Interact. 29(9), 604–618 (2013)CrossRefGoogle Scholar
  29. 29.
    Sáenz-de-Urturi, Z., García Zapirain, B., Méndez Zorrilla, A.: Elderly user experience to improve a Kinect-based game playability. Behav. Inf. Technol. 34(11), 1040–1051 (2015)CrossRefGoogle Scholar
  30. 30.
    Page, T.: Touchscreen mobile devices and older adults: a usability study. Int. J. Hum. Factors Ergon. 3(1), 65–85 (2014)CrossRefGoogle Scholar
  31. 31.
    Bobeth, J., Schmehl, S., Kruijff, E., Deutsch, S., Tscheligi, M.: Evaluating performance and acceptance of older adults using freehand gestures for TV menu control. In: Proceedings of 10th European conference on Interactive TV and Video, Berlin, Germany, 04–06 July, pp. 35–44. ACM (2012)Google Scholar
  32. 32.
    Gerling, K., Livingston, I., Nacke, L., Mandryk, R.: Full-body motion-based game interaction for older adults. In: Proceedings of SIGCHI Conference on Human Factors in Computing Systems, Austin, TX, USA, 05–10 May, pp. 1873–1882. ACM (2012)Google Scholar
  33. 33.
    Ferron, M., Mana, N., Mich, O.: Mobile for older adults: towards designing multimodal interaction. In: Proceedings of 14th International Conference on Mobile and Ubiquitous Multimedia, Linz, Austria, 30 November–02 December, pp. 373–378. ACM (2015)Google Scholar
  34. 34.
    Ouchi, K., Esaka, N., Tamura, Y., Hirahara, M., Doi, M.: Magic wand: an intuitive gesture remote control for home appliances. In: International Conference on Active Media Technology, Kagawa, Japan, 19–21 May (2005)Google Scholar
  35. 35.
    Ruser, H., Kosterski, Sz., Kargel, Ch.: Gesture-based universal optical remote control: concept, reconstruction principle and recognition results. In: IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Pisa (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Susan Vorwerg
    • 1
    Email author
  • Cornelia Eicher
    • 1
  • Heinrich Ruser
    • 2
  • Felix Piela
    • 3
  • Felix Obée
    • 3
  • André Kaltenbach
    • 4
  • Lars Mechold
    • 4
  1. 1.Charité – Universitätsmedizin BerlinBerlinGermany
  2. 2.Universität der Bundeswehr MünchenNeubibergGermany
  3. 3.August & Piela Konstruktiv GbRBerlinGermany
  4. 4.Laser Components GmbHOlchingGermany

Personalised recommendations