A Discomfort-Sensitive Chair for Pointing Out Mental Fatigue

  • André PimentaEmail author
  • Davide Carneiro
  • Paulo Novais
  • José Neves
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 376)


In our busy daily life, we often have the feeling of being exhausted, accompanied with a sense of performance degradation and increase of discomfort in the execution of even simple tasks. This often takes place in the workplace and in a silent way, influencing our productivity, our performance the number of errors or the quality of our production. This paper details a chair to be used in workplace environments that is sensitive to the onset of fatigue. Based on built-in accelerometers it recognizes signs of discomfort, which may be related to mental fatigue, to point out moments when an individual should consider taking a pause or a rest. This chair complements a previously developed software for the assessment of mental fatigue from the analysis of the individual’s interaction with the computer.


Ambient intelligence Fatigue Statistical analysis Clustering 



This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012) and project PEst-OE/EEI/UI0752/2014.


  1. 1.
    P.V. Bulat, Evaluation of methods for the determination of factors inducing fatigue in man at work. Ergonomics 14(1), 43–51 (1971)CrossRefGoogle Scholar
  2. 2.
    M.H. Liao, C. Drury, Posture, discomfort and performance in a vdt task. Ergonomics 43(3), 345–359 (2000)CrossRefGoogle Scholar
  3. 3.
    J.H.V. Dieen, Evaluation of work-rest schedules with respect to the effects of postural workload in standing work. Ergonomics 41(12), 1832–1844 (1998)CrossRefGoogle Scholar
  4. 4.
    T. Åkerstedt, A. Knutsson, P. Westerholm, T. Theorell, L. Alfredsson, G. Kecklund, Mental fatigue, work and sleep. J. Psychosom. Res. 57(5), 427–433 (2004)CrossRefGoogle Scholar
  5. 5.
    E. Hollnagel, D.D. Woods, Cognitive systems engineering: new wine in new bottles. Int. J. Man Mach. Stud. 18(6), 583–600 (1983)CrossRefGoogle Scholar
  6. 6.
    M. Paradowski, A. Fletcher, Using task analysis to improve usability of fatigue modelling software. Int. J. Human Comput. Stud. 60(1), 101–115 (2004)CrossRefGoogle Scholar
  7. 7.
    R. Parasuraman, G.F. Wilson, Putting the brain to work: neuroergonomics past, present, and future. Hum. Factors: J. Hum. Factors Ergon. Soc. 50(3), 468–474 (2008)CrossRefGoogle Scholar
  8. 8.
    A. Pimenta, D. Carneiro, P. Novais, J. Neves, Monitoring mental fatigue through the analysis of keyboard and mouse interaction patterns, in Hybrid Artificial Intelligent Systems (Springer, 2013), pp. 222–231Google Scholar
  9. 9.
    L.P. Perelli, Fatigue Stressors in Simulated Long-duration Flight. Effects on Performance, Information Processing, Subjective Fatigue, and Physiological Cost. Technical Report, DTIC Document (1980)Google Scholar
  10. 10.
    M. Charrad, N. Ghazzali, V. Boiteau, A. Niknafs, NbClust: an R package for determining the relevant number of clusters in a data set. J. Stat. Softw. 61(6), 1–36 (2014)Google 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.ALGORITMI-Universidade do MinhoBragaPortugal

Personalised recommendations