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The level of mental load during a functional task is reflected in oculometrics

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EMBEC & NBC 2017 (EMBEC 2017, NBC 2017)

Abstract

Modern occupations have increasingly become mentally demanding. This underlines the needs for investigation of the interaction of mental and physical workload. This study assessed the effects of mental load on ocular metrics and their consistency across days. Eighteen participants performed a five minute simulated computer work with three different levels of mental load in two days at least seven days apart. Eye movements in response to the task mental load level were recorded. Along with eye movements, task performance, and national aeronautics and space administration task load index (NASA-TLX) scores were acquired. Peak saccade velocity decreased, and pupil dilation range increased with the task load level and the response remained consistent across experimental days. Increased NASA-TLX score and reduced performance were in association with mental load demand. The study shows the feasibility of quantifying the mental load demands by monitoring oculometrics during a functional task such as computer work.

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References

  • 1. Stansfeld S, Candy B (2006) Psychosocial work environment and mental health—a meta-analytic review. Scand J Work Environ Health 443–462.

    Google Scholar 

  • 2. van der Linden D, Frese M, Sonnentag S (2003) The impact of mental fatigue on exploration in a complex computer task: rigidity and loss of systematic strategies. Hum Factors 45:483–494. doi: 10.1518/hfes.45.3.483.27256

  • 3. Di Stasi LL, Renner R, Staehr P, et al (2010) Saccadic peak velocity sensitivity to variations in mental workload. Aviat Space Environ Med 81:413–417. doi: 10.3357/ASEM.2579.2010

  • 4. Wu C, Liu Y (2007) Queuing network modeling of driver workload and performance. Intell Transp Syst IEEE Trans 8:528–537. doi: 10.1109/TITS.2007.903443

  • 5. Munoz DP, Broughton JR, Goldring JE, Armstrong IT (1998) Age-related performance of human subjects on saccadic eye movement tasks. Exp Brain Res 121:391–400. doi: 10.1007/s002210050473

  • 6. Srinivasan D, Erik S, David M, et al (2016) Effects of concurrent physical and cognitive demands on muscle activity and heart rate variability in a repetitive upper ‑ extremity precision task. Eur J Appl Physiol 116:227–239. doi:10.1007/s00421-015-3268-8

  • 7. Di Stasi LL, McCamy MB, Catena AA, et al (2013) Microsaccade and drift dynamics reflect mental fatigue. Eur J Neurosci 38:2389–2398. doi: 10.1111/ejn.12248

  • 8. Chaffin D, Andersson G, Martin B (1999) Occupational biomechanics.

    Google Scholar 

  • 9. Chen Y, Sundaram H (2006) Estimating complexity of 2D shapes. 2005 IEEE 7th Work Multimed Signal Process 3:2–5. doi: 10.1109/MMSP.2005.248668

  • 10. Sun C, Wang Y, Zheng J (2014) Dissecting pattern unlock: The effect of pattern strength meter on pattern selection. J Inf Secur Appl 19:308–320. doi: 10.1016/j.jisa.2014.10.009

  • 11. Hart, Sandra G (2006) NASA-task load index (NASA-TLX); 20 years later. Hum Factors Ergon Soc Annu Meting 904–908. doi: 10.1037/e577632012-009

  • 12. Nyström M, Holmqvist K (2010) An adaptive algorithm for fixation, saccade, and glissade detection in eyetracking data. Behav Res Methods 42:188–204. doi: 10.3758/BRM.42.1.188

  • 13. Savitzky A, Golay MJE (1964) Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Anal Chem 36:1627–1639. doi: 10.1021/ac60214a047

  • 14. Schiffman HR (1990) Sensation and perception: An integrated approach. John Wiley & Sons

    Google Scholar 

  • 15. Gowrisankaran S, Nahar NK, Hayes JR, Sheedy JE (2012) Asthenopia and Blink Rate Under Visual and Cognitive Loads. Optom Vis Sci 89:97–104. doi: 10.1097/OPX.0b013e318236dd88

  • 16. Sharek D (2011) A Useable, Online NASA-TLX Tool. Proc Hum Factors Ergon Soc Annu Meet 55:1375–1379. doi: 10.1177/1071181311551286

  • 17. Veltman JA, Gaillard AWK (1996) Physiological indices of workload in a simulated flight task. In: Biol. Psychol. pp 323–342

    Google Scholar 

  • 18. Ruiz-Rabelo JF, Navarro-Rodriguez E, Di-Stasi LL, et al (2015) Validation of the NASA-TLX Score in Ongoing Assessment of Mental Workload During a Laparoscopic Learning Curve in Bariatric Surgery. Obes Surg 25:2451–2456. doi: 10.1007/s11695-015-1922-1

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Correspondence to Afshin Samani .

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Marandi, R.Z., Samani, A., Madeleine, P. (2018). The level of mental load during a functional task is reflected in oculometrics. In: Eskola, H., Väisänen, O., Viik, J., Hyttinen, J. (eds) EMBEC & NBC 2017. EMBEC NBC 2017 2017. IFMBE Proceedings, vol 65. Springer, Singapore. https://doi.org/10.1007/978-981-10-5122-7_15

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  • DOI: https://doi.org/10.1007/978-981-10-5122-7_15

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  • Print ISBN: 978-981-10-5121-0

  • Online ISBN: 978-981-10-5122-7

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