Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-16T22:51:12.564Z Has data issue: false hasContentIssue false
  • English
  • Français

Psychophysiological responses to different levels of cognitive and physical workload in haptic interaction

Published online by Cambridge University Press:  19 May 2010

Domen Novak ,
Matjaž Mihelj  and
Marko Munih
Domen Novak*
Affiliation:
University of Ljubljana, Faculty of Electrical Engineering, Trzaska cesta 25, 1000 Ljubljana, Slovenia
Matjaž Mihelj
Affiliation:
University of Ljubljana, Faculty of Electrical Engineering, Trzaska cesta 25, 1000 Ljubljana, Slovenia
Marko Munih
Affiliation:
University of Ljubljana, Faculty of Electrical Engineering, Trzaska cesta 25, 1000 Ljubljana, Slovenia
*
*Corresponding author. E-mail: domen.novak@robo.fe.uni-lj.si
Get access Rights & Permissions [Opens in a new window]

Summary

Psychophysiological measurements, which serve as objective indicators of psychological state, have recently been introduced into human–robot interaction. However, their usefulness in haptic interaction is uncertain, since they are influenced by physical workload. This study analyses psychophysiological responses to a haptic task with three different difficulty levels and two different levels of physical load. Four physiological responses were recorded: heart rate, skin conductance, respiratory rate and skin temperature. Results show that mean respiratory rate, respiratory rate variability and skin temperature show significant differences between difficulty levels regardless of physical load and can be used to estimate cognitive workload in haptic interaction.

Keywords

Haptic interfacesPsychophysiologyVirtual realityHuman factorsMultimodal interfaces
Type
Article
Information
Robotica , Volume 29 , Issue 3 , May 2011 , pp. 367 - 374
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Andreassi, J. J., Psychophysiology: Human Behaviour and Physiological Response (Lawrence Erlbaum Associates. London, UK, 2000).Google Scholar
2.Meehan, M., Insko, B., Whitton, M. and Brooks, F. P., “Physiological measures of presence in stressful virtual environments,” ACM T. Graphic. 21, 645–653 (2002).CrossRefGoogle Scholar
3.Slater, M., Guger, C., Edlinger, G., Leeb, R., Pfurtscheller, G., Antley, A., Garau, M., Brogni, A., Steed, A. and Friedman, D., “Analysis of physiological responses to a social situation in an immersive virtual environment,” Presence: Teleop. Virt. 15, 553–569 (2006).CrossRefGoogle Scholar
4.Rani, P., Sarkar, N., Smith, C. A. and Kirby, L. D., “Anxiety detecting robotic system – towards implicit human–robot collaboration,” Robotica 22, 85–95 (2004).CrossRefGoogle Scholar
5.Kulić, D. and Croft, E., “Physiological and subjective responses to articulated robot motion,” Robotica 25, 13–27 (2007).CrossRefGoogle Scholar
6.Liu, C., Conn, K., Sarkar, N. and Stone, W., “Online affect detection and robot behavior adaptation for intervention of children with autism,” IEEE Trans. Robot. 24, 883–896 (2008).Google Scholar
7.Yao, Y. J., Chang, Y. M., Xie, X. P., Cao, X. S., Sun, X. Q. and Wu, Y. H., “Heart rate and respiration responses to real traffic pattern flight,” Appl. Psychophysiol. Biofeedback 33, 203–209 (2008).CrossRefGoogle ScholarPubMed
8.Roth, D. L., Bachtler, S. D. and Fillingim, R. B., “Acute emotional and cardiovascular effects of stressful mental work during aerobic exercise,” Psychophysiology 27, 694–701 (1990).CrossRefGoogle ScholarPubMed
9.Webb, H. E., Weldy, M. L., Fabianke-Kadue, E. C., Orndorff, G. R., Kamimori, G. H. and Acevedo, E. O., “Psychological stress during exercise: cardiorespiratory and hormonal responses,” Eur. J. Appl. Physiol. 104, 973–981 (2008).CrossRefGoogle ScholarPubMed
10.van der Linde, R. Q. and Lammertse, P., “HapticMaster – a generic force controlled robot for human interaction,” Ind. Robot 30, 515–524 (2003).CrossRefGoogle Scholar
11.Fowles, D. C., Christie, M. J., Edelberg, R., Grings, W. W., Lykken, D. T. and Venables, P. H., “Committee report: Publication recommendations for electrodermal measurements,” Psychophysiology 18, 232–239 (1981).CrossRefGoogle ScholarPubMed
12.Bradley, M. M. and Lang, P. J., “Measuring emotion: the self-assessment manikin and the semantic differential,” J. Behav. Ther. Exp. Psychiatr. 25, 49–59 (1994).CrossRefGoogle ScholarPubMed
13.Mehrabian, A., “Pleasure-arousal-dominance: A general framework for describing and measuring individual differences in temperament,” Curr. Psychol. 14, 261–292 (1996).CrossRefGoogle Scholar
14.Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, “Heart rate variability: Standards of measurement, physiological interpretation, and clinical use,” Eur. Heart J. 17, 354–381 (1996).CrossRefGoogle Scholar
15.Veltman, J. A. and Gaillard, A. W. K., “Physiological workload reactions to increasing levels of task difficulty,” Ergonomics 41, 656–669 (1998).CrossRefGoogle ScholarPubMed
16.Backs, R. W., Lenneman, J. K., Wetzel, J. M. and Green, P., “Cardiac measures of driver workload during simulated driving with and without visual occlusion,” Hum. Factors 45, 525–538 (2003).CrossRefGoogle ScholarPubMed
17.Detenber, B. H., Simons, R. F. and Bennett, G. G., “Roll ‘em!: the effects of picture motion on emotional responses,” J. Broadcast. Electron. 42, 113–127 (1998).CrossRefGoogle Scholar
18.Collet, C., Averty, P. and Dittmar, A., “Autonomic nervous system and subjective ratings of strain in air-traffic control,” Appl. Ergon. 40, 23–32 (2009).CrossRefGoogle ScholarPubMed
19.Nikula, R., “Psychological correlates of nonspecific skin conductance responses,” Psychophysiology 28, 86–90 (1991).CrossRefGoogle ScholarPubMed
20.Haarmann, A., Boucsein, W. and Schaefer, F., “Combining electrodermal responses and cardiovascular measures for probing adaptive automation during simulated flight,” Appl. Ergon. 40, 1026–1040 (2009).CrossRefGoogle ScholarPubMed
21.Brookings, J. B., Wilson, G. F. and Swain, C. R., “Psychophysiological responses to changes in workload during simulated air traffic control,” Biol. Psychol. 42, 361–377 (1996).CrossRefGoogle ScholarPubMed
22.Boiten, F., “Component analysis of task-related respiratory patterns,” Int. J. Psychophysiol. 15, 91–104 (1993).CrossRefGoogle ScholarPubMed
23.Ohsuga, M., Shimono, F. and Genno, H., “Assessment of phasic work stress using autonomic indices,” Int. J. Psychophysiol. 40, 211–220 (2001).CrossRefGoogle ScholarPubMed
24.Min, B. C., Chung, S. C., Park, S. J., Kim, C. J., Sim, M.-K. and Sakamoto, K., “Autonomic responses of young passengers contingent to the speed and driving mode of a vehicle,” Int. J. Ind. Ergonom. 29, 187–198 (2002).CrossRefGoogle Scholar
25.Koenig, A. C., Somaini, L., Pulfer, M., Holenstein, T., Omlin, X., Wieser, M. and Riener, R., “Model-Based Heart Rate Prediction During Lokomat Walking,” Proceedings of the 31st Annual International Conference of IEEE EMBC, Minneapolis (2009).Google Scholar