Human-Computer Interaction

INTERACT 2015: Human-Computer Interaction – INTERACT 2015 pp 156-164 | Cite as

Comparing Fatigue When Using Large Horizontal and Vertical Multi-touch Interaction Displays

  • Shiroq Al-Megren
  • Ahmed Kharrufa
  • Jonathan Hook
  • Amey Holden
  • Selina Sutton
  • Patrick Olivier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9299)

Abstract

We report on a user study that compared muscle fatigue experienced when using a large multi-touch display in horizontal and vertical configurations over a one-hour period. Muscle fatigue is recognized as the reduction in a muscle’s capacity to generate force or power output and was measured objectively and subjectively before and after a puzzle-solving task. While subjective measures showed a significant level of overall arm muscle fatigue after the task for both configurations, objective measures showed a significant level of muscle fatigue on the middle deltoids and the non-dominant extensor digitorum for the vertical configuration only. We discuss the design implications of these findings and suggest relevant future areas of investigation.

Keywords

Large displays Interaction Tabletops Fatigue Ergonomics 

References

  1. 1.
    Vøllestad, N.K.: Measurement of human muscle fatigue. J. Neurosci. Methods 74, 219–227 (1997)CrossRefGoogle Scholar
  2. 2.
    Wahlström, J.: Ergonomics, musculoskeletal disorders and computer work. Occ. Med. 55, 168–176 (2005)CrossRefGoogle Scholar
  3. 3.
    Meyer, S., Cohen, O., Nilsen, E.: Device comparisons for goal-directed drawing tasks. In: CHI 1995 Conference Companion, pp. 251–252. ACM, Boston (1994)Google Scholar
  4. 4.
    Sears, A., Shneiderman, B.: High precision touchscreens: design strategies and comparisons with a mouse. Int J Man-Mach Stud 34, 593–613 (1991)CrossRefGoogle Scholar
  5. 5.
    Barriera-Viruet, H., Sobeih, T.M., Daraiseh, N., Salem, S.: Questionnaires vs observational and direct measurements: a systematic review. In: TIES 2006, vol. 7, pp. 261–284 (2006)Google Scholar
  6. 6.
    Young, J.G., Trudeau, M.B., Odell, D., Marinelli, K., Dennerlein, J.T.: Wrist and shoulder posture and muscle activity during touch-screen tablet use. WORK 45, 59–71 (2013)Google Scholar
  7. 7.
    Lozano, C., Jindrich, D., Kahol, K.: The impact on musculoskeletal system during multitouch tablet interactions. In: ACM CHI 2011, pp. 825–828. ACM, Vancouver (2011)Google Scholar
  8. 8.
    Ichino, J., Isoda, K., Hanai, A., Ueda, T.: Effects of the display angle in museums on user’s cognition, behavior, and subjective responses. In: CHI 2013, pp. 2979–2988. ACM, Paris (2013)Google Scholar
  9. 9.
    Muller-Tomfelde, C., Wessels, A., Schremmer, C.: Tilted tabletops: in between horizontal and vertical workspaces. In: TABLETOP 2008, pp. 49–56 (2008)Google Scholar
  10. 10.
    Zerpa, C., Lopez, N., Przysucha, E., Sanzo, P.: The effect of common teaching tools on upper extremity muscle activity. Education 4, 160–166 (2014)Google Scholar
  11. 11.
    Morris, M.R., Brush, A.J.B., Meyers, B.R.: A field study of knowledge workers’; use of interactive horizontal displays. In: TABLETOP 2008, pp. 105–112 (2008)Google Scholar
  12. 12.
    Wigdor, D., Perm, G., Ryall, K., Esenther, A., Chia, S.: Living with a tabletop: Analysis and observations of long term office use of a multi-touch table. In: TABLETOP’07, pp. 60–67 (2007)Google Scholar
  13. 13.
    Criswell, E.: Cram’s Introduction to Surface Electromyography. Jones and Barlett, London (2011)Google Scholar
  14. 14.
    Borg, G., Borg, E.: A new generation for scaling methods: level-anchored ratio scaling. Psychologica 28, 15–45 (2001)Google Scholar
  15. 15.
    Cioni, R., Giannini, F., Paradiso, C., Battistini, N., Navona, C., Starita, A.: Sex differences in surface EMG interference pattern power spectrum. J. Appl. Physiol. 77, 2163–2168 (1994)Google Scholar
  16. 16.
    Hincapi-Ramos, J.D., Guo, X., Moghadasian, P., Irani, P.: Consumed endurance: a metric to quantify arm fatigue of mid-air interactions. In: CHI 2014, pp. 1063–1072. ACM, Toronto (2014)Google Scholar
  17. 17.
    Al-Mulla, M.R., Sepulveda, F., Colley, M.: A review of non-invasive techniques to detect and predict localised muscle fatigue. Sensors 11, 3545–3594 (2011)CrossRefGoogle Scholar
  18. 18.
    Peres, S.C., Nguyen, V., Kortum, P.T., Akladios, M., Wood, S.B., Muddimer, A.: Software ergonomics: relating subjective and objective measures. In: CHI 2009 EA, pp. 3949–3954. ACM, Boston (2009)Google Scholar
  19. 19.
    Sherwood, L.: Human physiology: from cells to systems. Cengage Learning, USA (2012)Google Scholar
  20. 20.
    Phinyomark, A., Thongpanja, S., Hu, H., Phukpattaranont, P., Limsakul, C.: The usefulness of mean and median frequencies in electromyography analysis. In: Naik, G.R. (ed.) Computational Intelligence in Electromyography Analysis – A Perspective on Current Applications and Future Challenges, pp. 195–220 (2012)Google Scholar
  21. 21.
    Murata, A., Ishihara, H.: Evaluation of shoulder muscular fatigue induced during mouse operation in a VDT task. IEICE Trans. Inf. Syst. E88-D, 223–229 (2005)CrossRefGoogle Scholar
  22. 22.
    Lawrence, J.H., De Luca, C.J.: Myoelectric signal versus force relationship in different human muscles. J Appl Physiol Respir Environ Exerc Physiol 54, 1653–1659 (1983)Google Scholar
  23. 23.
  24. 24.

Copyright information

© IFIP International Federation for Information Processing 2015

Authors and Affiliations

  • Shiroq Al-Megren
    • 1
  • Ahmed Kharrufa
    • 2
  • Jonathan Hook
    • 3
  • Amey Holden
    • 2
  • Selina Sutton
    • 2
  • Patrick Olivier
    • 2
  1. 1.School of ComputingUniversity of LeedsLeedsUK
  2. 2.Culture LabNewcastle UniversityNewcastle upon TyneUK
  3. 3.Department of Theatre, Film and TelevisionUniversity of YorkYorkUK

Personalised recommendations