Detection of Distraction and Fatigue in Groups through the Analysis of Interaction Patterns with Computers

  • André PimentaEmail author
  • Davide Carneiro
  • Paulo Novais
  • José Neves
Part of the Studies in Computational Intelligence book series (SCI, volume 570)


Nowadays, our lifestyle can lead to a scatter of focus, especially when we attend to several tasks in parallel or have to filter the important information from all the remaining one. In the context of a computer this usually means interacting with several applications simultaneously. Over the day, this significant demand on our brain results in the emergence of fatigue, making an individual more prone to distractions. Good management of the working time and effort invested in each task, as well as the effect of breaks at work, can result in better performance and better mental health, delaying the effects of fatigue. This paper presents a non-intrusive and non-invasive method for measuring distraction and fatigue in an individual and in a group of people. The main aim is to allow team managers to better understand the state of their collaborators, thus preparing them to take better decisions concerning their management.


Distraction Fatigue Task Performance Behavioural Biometrics Distributed Intelligence Pattern Analysis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Alm, H., Nilsson, L.: The effects of a mobile telephone task on driver behaviour in a car following situation. Accident Analysis & Prevention 27(5), 707–715 (1995)CrossRefGoogle Scholar
  2. 2.
    Bartlett, F.C.: Ferrier lecture: fatigue following highly skilled work. Proceedings of the Royal Society of London. Series B-Biological Sciences 131(864), 247–257 (1943)CrossRefGoogle Scholar
  3. 3.
    Boksem, M.A., Meijman, T.F., Lorist, M.M.: Effects of mental fatigue on attention: an erp study. Cognitive Brain Research 25(1), 107–116 (2005)CrossRefGoogle Scholar
  4. 4.
    Carneiro, D., Novais, P., Catalão, F., Marques, J., Pimenta, A., Neves, J.: Dynamically improving collective environments through mood induction procedures. In: van Berlo, A., Hallenborg, K., Rodríguez, J.M.C., Tapia, D.I., Novais, P. (eds.) Ambient Intelligence - Software & Applications. AISC, vol. 219, pp. 33–40. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  5. 5.
    Faber, L.G., Maurits, N.M., Lorist, M.M.: Mental fatigue affects visual selective attention. PloS One 7(10), e48073 (2012)CrossRefGoogle Scholar
  6. 6.
    Horvitz, E., Jacobs, A., Hovel, D.: Attention-sensitive alerting. In: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, pp. 305–313. Morgan Kaufmann Publishers Inc. (1999)Google Scholar
  7. 7.
    Hwang, K., Yang, C.: Automated Inattention and Fatigue Detection System in Distance Education for Elementary School Students. Journal of Educational Technology & Society 12, 22–35 (2009)Google Scholar
  8. 8.
    Mayer, R.E., Moreno, R.: A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology 90(2), 312 (1998)CrossRefGoogle Scholar
  9. 9.
    Meijman, T.F.: Mental fatigue and the efficiency of information processing in relation to work times. International Journal of Industrial Ergonomics 20(1), 31–38 (1997)CrossRefGoogle Scholar
  10. 10.
    van der Linden, D., Frese, M., Meijman, T.F.: Mental fatigue and the control of cognitive processes: effects on perseveration and planning. Acta Psychologica 113(1), 45–65 (2003)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • André Pimenta
    • 1
    Email author
  • Davide Carneiro
    • 1
  • Paulo Novais
    • 1
  • José Neves
    • 1
  1. 1.CCTC/DIUniversidade do MinhoBragaPortugal

Personalised recommendations