Research Article
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Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions

Year 2021, Volume: 10 Issue: 3, 306 - 312, 22.09.2021

Barış Özsever Leyla Tavacıoğlu

https://doi.org/10.33714/masteb.976409

Abstract

Mental workload (MWL) has a negative effect on the functional states of watchkeeping officers that ultimately causes collisions and groundings at sea. The aim of this study is to measure the MWL of officers during different navigation conditions. This study was conducted in a bridge simulator with 11 participants. Heart rate variability (HRV) measurements were taken during the 4 steps which have different difficulty levels and subjective assessments were taken at the end of each step by using NASA-TLX. The results of the measurements showed that different levels of navigation tasks caused significantly different levels of MWL and HRV values and MWL and HRV increased when task difficulty increased. Additionally, the correlation between MWL perceived by the participants and the heart rate variability values of the participants was found statistically significant. This study provides an example of predicting MWL for routine navigation operations by using physiological measures in maritime transportation.

Keywords

Heart rate variability Mental workload NASA-TLX Ship navigation

Supporting Institution

Scientific Research Projects Department of Istanbul Technical University

Project Number

41710

Thanks

This study was supported by the Scientific Research Projects Department of Istanbul Technical University. Project Number: 41710. The authors would like to thank the ocean-going marine officers who are the participants in this experimental research for their valuable contributions.

References

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  • Akhtar, M. J., & Bouwer Utne, I. (2015). Common patterns in aggregated accident analysis charts from human fatigue-related groundings and collisions at sea. Maritime Policy & Management, 42(2), 186-206. https://doi.org/10.1080/03088839.2014.926032
  • Alberdi, A., Aztiria, A., & Basarab, A. (2016). Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review. Journal of Biomedical Informatics, 59, 49-75. https://doi.org/10.1016/j.jbi.2015.11.007
  • Backs, R. W., Navidzadeh, H. T., & Xu, X. (2000). Cardiorespiratory indices of mental workload during simulated air traffic control. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 44(13), 89-92. https://doi.org/10.1177/154193120004401323
  • De Rivecourt, M., Kuperus, M., Post, W., & Mulder, L. (2008). Cardiovascular and eye activity measures as indices for momentary changes in mental effort during simulated flight. Ergonomics, 51(9), 1295-1319. https://doi.org/10.1080/00140130802120267
  • De Waard, D. (1996). The measurement of drivers’ mental workload. The Traffic Research Center VSC.
  • Delaney, J., & Brodie, D. (2000). Effects of short-term psychological stress on the time and frequency domains of heart-rate variability. Perceptual and Motor Skills, 91(2), 515-524. https://doi.org/10.2466/pms.2000.91.2.515
  • Embrey, D., Blackett, C., Marsden, P., & Peachey, J. (2006). Development of a human cognitive workload assessment tool. MCA Final Report, Lancashire.
  • Fairclough, S. H., Venables, L., & Tattersall, A. (2005). The influence of task demand and learning on the psychophysiological response. International Journal of Psychophysiology, 56(2), 171-184. https://doi.org/10.1016/j.ijpsycho.2004.11.003
  • Finsen, L., Søgaard, K., Jensen, C., Borg, V., & Christensen, H. (2001). Muscle activity and cardiovascular response during computer-mouse work with and without memory demands. Ergonomics, 44(14), 1312-1329. https://doi.org/10.1080/00140130110099065
  • Fournier, L. R., Wilson, G. F., & Swain, C. R. (1999). Electrophysiological, behavioral, and subjective indexes of workload when performing multiple tasks: Manipulations of task difficulty and training. International Journal of Psychophysiology, 31(2), 129-145. https://doi.org/10.1016/S0167-8760(98)00049-X
  • Gao, Q., Wang, Y., Song, F., Li, Z., & Dong, X. (2013). Mental workload measurement for emergency operating procedures in digital nuclear power plants. Ergonomics, 56(7), 1070-1085. https://doi.org/10.1080/00140139.2013.790483
  • Gould, K. S., Røed, B. K., Saus, E.-R., Koefoed, V. F., Bridger, R. S., & Moen, B. E. (2009). Effects of navigation method on workload and performance in simulated high-speed ship navigation. Applied Ergonomics, 40(1), 103-114. https://doi.org/10.1016/j.apergo.2008.01.001
  • Grabowski, M., & Sanborn, S. D. (2003). Human performance and embedded intelligent technology in safety-critical systems. International Journal of Human-Computer Studies, 58(6), 637-670. https://doi.org/10.1016/S1071-5819(03)00036-3
  • Grech, M., Horberry, T., & Koester, T. (2008). Human factors in the maritime domain. 1st ed. CRC Press. Kahneman, D. (1973). Attention and effort (Vol. 1063). Prentice-Hall.
  • Kurt, R. E., Khalid, H., Turan, O., Houben, M., Bos, J., & Helvacioglu, I. H. (2016). Towards human-oriented norms: Considering the effects of noise exposure on board ships. Ocean Engineering, 120, 101-107. https://doi.org/10.1016/j.oceaneng.2016.03.049
  • Lean, Y., & Shan, F. (2012). Brief review on physiological and biochemical evaluations of human mental workload. Human Factors and Ergonomics in Manufacturing & Service Industries, 22(3), 177-187. https://doi.org/10.1002/hfm.20269
  • Lehrer, P., Karavidas, M., Lu, S.-E., Vaschillo, E., Vaschillo, B., & Cheng, A. (2010). Cardiac data increase association between self-report and both expert ratings of task load and task performance in flight simulator tasks: An exploratory study. International Journal of Psychophysiology, 76(2), 80-87. https://doi.org/10.1016/j.ijpsycho.2010.02.006
  • Louie, V. W., & Doolen, T. L. (2007). A study of factors that contribute to maritime fatigue. Marine Technology, 44(2), 82-92. https://doi.org/10.5957/mt1.2007.44.2.82
  • Optical Pulse Sensor User Guide. (2016). Optical Pulse Sensor User Guide Revision 1.6. Shimmer.
  • Orlandi, L., & Brooks, B. (2018). Measuring mental workload and physiological reactions in marine pilots: Building bridges towards redlines of performance. Applied Ergonomics, 69, 74-92. https://doi.org/10.1016/j.apergo.2018.01.005
  • Özsever, B., & Tavacıoğlu, L. (2018). Analysing the effects of working period on psychophysiological states of seafarers. International Maritime Health, 69(2), 84-93. https://doi.org/10.5603/IMH.2018.0013
  • Ramshur, J. T. (2010). Design, evaluation, and application of heart rate variability analysis software (HRVAS). [M.Sc. Thesis. University of Memphis].
  • Robert, G., Hockey, J., Healey, A., Crawshaw, M., Wastell, D. G., & Sauer, J. (2003). Cognitive demands of collision avoidance in simulated ship control. Human Factors, 45(2), 252-265. https://doi.org/10.1518/hfes.45.2.252.27240
  • Selvaraj, N., Jaryal, A., Santhosh, J., Deepak, K. K., & Anand, S. (2008). Assessment of heart rate variability derived from finger-tip photoplethysmography as compared to electrocardiography. Journal of Medical Engineering & Technology, 32(6), 479-484. https://doi.org/10.1080/03091900701781317
  • Sharma, N., & Gedeon, T. (2012). Objective measures, sensors and computational techniques for stress recognition and classification: A survey. Computer Methods and Programs in Biomedicine, 108(3), 1287-1301. https://doi.org/10.1016/j.cmpb.2012.07.003
  • Splawn, J. M., & Miller, M. E. (2013). Prediction of perceived workload from task performance and heart rate measures. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 57(1), 778-782. https://doi.org/10.1177/1541931213571170
  • Veltman, J., & Gaillard, A. (1998). Physiological workload reactions to increasing levels of task difficulty. Ergonomics, 41(5), 656-669. https://doi.org/10.1080/001401398186829
  • Wu, Y., Miwa, T., & Uchida, M. (2017). Using physiological signals to measure operator’s mental workload in shipping–an engine room simulator study. Journal of Marine Engineering & Technology, 16(2), 61-69. https://doi.org/10.1080/20464177.2016.1275496
  • Yan, S., Wei, Y., & Tran, C. C. (2019). Evaluation and prediction mental workload in user interface of maritime operations using eye response. International Journal of Industrial Ergonomics, 71, 117-127. https://doi.org/10.1016/j.ergon.2019.03.002
  • Young, M. S., & Stanton, N. A. (2002). Malleable attentional resources theory: a new explanation for the effects of mental underload on performance. Human Factors, 44(3), 365-375. https://doi.org/10.1518/0018720024497709

Year 2021, Volume: 10 Issue: 3, 306 - 312, 22.09.2021

Barış Özsever Leyla Tavacıoğlu

https://doi.org/10.33714/masteb.976409

Abstract

Project Number

41710

References

  • Aimie-Salleh, N., Ghani, N. A. A., Hasanudin, N., & Shafie, S. N. S. (2019). Heart rate variability recording system using photoplethysmography sensor. In T. Aslanidis, (Ed.), Autonomic nervous system monitoring (pp. 29-43). IntechOpen.
  • Akhtar, M. J., & Bouwer Utne, I. (2015). Common patterns in aggregated accident analysis charts from human fatigue-related groundings and collisions at sea. Maritime Policy & Management, 42(2), 186-206. https://doi.org/10.1080/03088839.2014.926032
  • Alberdi, A., Aztiria, A., & Basarab, A. (2016). Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review. Journal of Biomedical Informatics, 59, 49-75. https://doi.org/10.1016/j.jbi.2015.11.007
  • Backs, R. W., Navidzadeh, H. T., & Xu, X. (2000). Cardiorespiratory indices of mental workload during simulated air traffic control. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 44(13), 89-92. https://doi.org/10.1177/154193120004401323
  • De Rivecourt, M., Kuperus, M., Post, W., & Mulder, L. (2008). Cardiovascular and eye activity measures as indices for momentary changes in mental effort during simulated flight. Ergonomics, 51(9), 1295-1319. https://doi.org/10.1080/00140130802120267
  • De Waard, D. (1996). The measurement of drivers’ mental workload. The Traffic Research Center VSC.
  • Delaney, J., & Brodie, D. (2000). Effects of short-term psychological stress on the time and frequency domains of heart-rate variability. Perceptual and Motor Skills, 91(2), 515-524. https://doi.org/10.2466/pms.2000.91.2.515
  • Embrey, D., Blackett, C., Marsden, P., & Peachey, J. (2006). Development of a human cognitive workload assessment tool. MCA Final Report, Lancashire.
  • Fairclough, S. H., Venables, L., & Tattersall, A. (2005). The influence of task demand and learning on the psychophysiological response. International Journal of Psychophysiology, 56(2), 171-184. https://doi.org/10.1016/j.ijpsycho.2004.11.003
  • Finsen, L., Søgaard, K., Jensen, C., Borg, V., & Christensen, H. (2001). Muscle activity and cardiovascular response during computer-mouse work with and without memory demands. Ergonomics, 44(14), 1312-1329. https://doi.org/10.1080/00140130110099065
  • Fournier, L. R., Wilson, G. F., & Swain, C. R. (1999). Electrophysiological, behavioral, and subjective indexes of workload when performing multiple tasks: Manipulations of task difficulty and training. International Journal of Psychophysiology, 31(2), 129-145. https://doi.org/10.1016/S0167-8760(98)00049-X
  • Gao, Q., Wang, Y., Song, F., Li, Z., & Dong, X. (2013). Mental workload measurement for emergency operating procedures in digital nuclear power plants. Ergonomics, 56(7), 1070-1085. https://doi.org/10.1080/00140139.2013.790483
  • Gould, K. S., Røed, B. K., Saus, E.-R., Koefoed, V. F., Bridger, R. S., & Moen, B. E. (2009). Effects of navigation method on workload and performance in simulated high-speed ship navigation. Applied Ergonomics, 40(1), 103-114. https://doi.org/10.1016/j.apergo.2008.01.001
  • Grabowski, M., & Sanborn, S. D. (2003). Human performance and embedded intelligent technology in safety-critical systems. International Journal of Human-Computer Studies, 58(6), 637-670. https://doi.org/10.1016/S1071-5819(03)00036-3
  • Grech, M., Horberry, T., & Koester, T. (2008). Human factors in the maritime domain. 1st ed. CRC Press. Kahneman, D. (1973). Attention and effort (Vol. 1063). Prentice-Hall.
  • Kurt, R. E., Khalid, H., Turan, O., Houben, M., Bos, J., & Helvacioglu, I. H. (2016). Towards human-oriented norms: Considering the effects of noise exposure on board ships. Ocean Engineering, 120, 101-107. https://doi.org/10.1016/j.oceaneng.2016.03.049
  • Lean, Y., & Shan, F. (2012). Brief review on physiological and biochemical evaluations of human mental workload. Human Factors and Ergonomics in Manufacturing & Service Industries, 22(3), 177-187. https://doi.org/10.1002/hfm.20269
  • Lehrer, P., Karavidas, M., Lu, S.-E., Vaschillo, E., Vaschillo, B., & Cheng, A. (2010). Cardiac data increase association between self-report and both expert ratings of task load and task performance in flight simulator tasks: An exploratory study. International Journal of Psychophysiology, 76(2), 80-87. https://doi.org/10.1016/j.ijpsycho.2010.02.006
  • Louie, V. W., & Doolen, T. L. (2007). A study of factors that contribute to maritime fatigue. Marine Technology, 44(2), 82-92. https://doi.org/10.5957/mt1.2007.44.2.82
  • Optical Pulse Sensor User Guide. (2016). Optical Pulse Sensor User Guide Revision 1.6. Shimmer.
  • Orlandi, L., & Brooks, B. (2018). Measuring mental workload and physiological reactions in marine pilots: Building bridges towards redlines of performance. Applied Ergonomics, 69, 74-92. https://doi.org/10.1016/j.apergo.2018.01.005
  • Özsever, B., & Tavacıoğlu, L. (2018). Analysing the effects of working period on psychophysiological states of seafarers. International Maritime Health, 69(2), 84-93. https://doi.org/10.5603/IMH.2018.0013
  • Ramshur, J. T. (2010). Design, evaluation, and application of heart rate variability analysis software (HRVAS). [M.Sc. Thesis. University of Memphis].
  • Robert, G., Hockey, J., Healey, A., Crawshaw, M., Wastell, D. G., & Sauer, J. (2003). Cognitive demands of collision avoidance in simulated ship control. Human Factors, 45(2), 252-265. https://doi.org/10.1518/hfes.45.2.252.27240
  • Selvaraj, N., Jaryal, A., Santhosh, J., Deepak, K. K., & Anand, S. (2008). Assessment of heart rate variability derived from finger-tip photoplethysmography as compared to electrocardiography. Journal of Medical Engineering & Technology, 32(6), 479-484. https://doi.org/10.1080/03091900701781317
  • Sharma, N., & Gedeon, T. (2012). Objective measures, sensors and computational techniques for stress recognition and classification: A survey. Computer Methods and Programs in Biomedicine, 108(3), 1287-1301. https://doi.org/10.1016/j.cmpb.2012.07.003
  • Splawn, J. M., & Miller, M. E. (2013). Prediction of perceived workload from task performance and heart rate measures. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 57(1), 778-782. https://doi.org/10.1177/1541931213571170
  • Veltman, J., & Gaillard, A. (1998). Physiological workload reactions to increasing levels of task difficulty. Ergonomics, 41(5), 656-669. https://doi.org/10.1080/001401398186829
  • Wu, Y., Miwa, T., & Uchida, M. (2017). Using physiological signals to measure operator’s mental workload in shipping–an engine room simulator study. Journal of Marine Engineering & Technology, 16(2), 61-69. https://doi.org/10.1080/20464177.2016.1275496
  • Yan, S., Wei, Y., & Tran, C. C. (2019). Evaluation and prediction mental workload in user interface of maritime operations using eye response. International Journal of Industrial Ergonomics, 71, 117-127. https://doi.org/10.1016/j.ergon.2019.03.002
  • Young, M. S., & Stanton, N. A. (2002). Malleable attentional resources theory: a new explanation for the effects of mental underload on performance. Human Factors, 44(3), 365-375. https://doi.org/10.1518/0018720024497709
There are 31 citations in total.

Details

Primary Language English
Subjects Maritime Engineering (Other)
Journal Section Research Article
Authors

Barış Özsever 0000-0003-4926-2477

Leyla Tavacıoğlu 0000-0002-9919-8226

Project Number 41710
Publication Date September 22, 2021
Submission Date July 30, 2021
Acceptance Date September 6, 2021
Published in Issue Year 2021 Volume: 10 Issue: 3

Cite

APA Özsever, B., & Tavacıoğlu, L. (2021). Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions. Marine Science and Technology Bulletin, 10(3), 306-312. https://doi.org/10.33714/masteb.976409
AMA Özsever B, Tavacıoğlu L. Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions. Mar. Sci. Tech. Bull. September 2021;10(3):306-312. doi:10.33714/masteb.976409
Chicago Özsever, Barış, and Leyla Tavacıoğlu. “Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions”. Marine Science and Technology Bulletin 10, no. 3 (September 2021): 306-12. https://doi.org/10.33714/masteb.976409.
EndNote Özsever B, Tavacıoğlu L (September 1, 2021) Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions. Marine Science and Technology Bulletin 10 3 306–312.
IEEE B. Özsever and L. Tavacıoğlu, “Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions”, Mar. Sci. Tech. Bull., vol. 10, no. 3, pp. 306–312, 2021, doi: 10.33714/masteb.976409.
ISNAD Özsever, Barış - Tavacıoğlu, Leyla. “Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions”. Marine Science and Technology Bulletin 10/3 (September 2021), 306-312. https://doi.org/10.33714/masteb.976409.
JAMA Özsever B, Tavacıoğlu L. Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions. Mar. Sci. Tech. Bull. 2021;10:306–312.
MLA Özsever, Barış and Leyla Tavacıoğlu. “Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions”. Marine Science and Technology Bulletin, vol. 10, no. 3, 2021, pp. 306-12, doi:10.33714/masteb.976409.
Vancouver Özsever B, Tavacıoğlu L. Measuring Mental Workload and Heart Rate Variability of Officers During Different Navigation Conditions. Mar. Sci. Tech. Bull. 2021;10(3):306-12.
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