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Modeling and Estimation of Physiological, Psychological and Sensory Indicators for Working Capacity

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Advances in Neuroergonomics and Cognitive Engineering (AHFE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1201))

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Abstract

The cartographic basis of the proposed model contains data reflecting person functional status (FS). The FS comprises an integral composite score summarizing the available characteristics, functions and attributes of a person. This, in turn, can determine performance, directly and indirectly, on an activity or a task. FS indices reflect the current level of professional working capacity (PWC), the difficulty level of the activity or task as well as the nature of the influence of the working environment on the human organism. The mapping elements are selected as a function of the spectrum of methods available for estimating FS and PWC. These include physiological, psychological, and sensory indicators. In addition, depending on the conditions, the methods can distinguish between direct and indirect influence on performance. Methods like these can assist in identifying factors affecting specific FS, such as extensive, intensive, monotonous work, fatigue, hypokinesia and psycho-emotional stress.

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References

  1. Popovich, V.V., Leontev, Y.B., Ermolenko, A.A.: Method of visual library of functions development. In: Proceedings of the International Conference on Intelligent Information Technology. Beijing, 22–25 September, pp. 69–74 (2002)

    Google Scholar 

  2. Masakowski, Y.R., Aguiar, S.K.: Human performance in virtual environ ments. In: Cai, Y. (ed.) Computing with Instinct. Lecture Notes in Computer Science, vol. 5897, 107–118 (2011). https://doi.org/10.1007/978-3-642-19757-4_7

  3. Verkholyak, O.V., Kaya, H., Karpov, A.A.: Modeling short-term and long- term dependencies of the speech signal for paralinguistic emotion classification. In: SPIIRAS Proceedings, vol. 18, pp. 30–56 (2019). https://doi.org/10.15622/sp.18.1.30-56

  4. Lytaev, S., Shostak, V.: Collective and personal resilience of the military experts in extreme conditions. In: Kaur, G., Awasthy, S., Mandal, M.K. (eds.) Psychometric Testing in Armed Forces: Issues and Challenges, pp. 210–222, Pentagon Press, New Delhi (2012)

    Google Scholar 

  5. Pascalis, V., Fracasso, F., Corr, P.J.: Personality and augmenting/reducing (A/R) in auditory event-related potentials (ERPs) during emotional visual stimulation. Sci. Rep. 7, Article no. 41588 (2017). https://doi.org/10.1038/srep41588

  6. Shostak, V.I., Lytaev, S.A., Golubeva, L.V.: Topography of afferent and efferent flows in the mechanisms of auditory selective attention. Neurosci. Behav. Physiol. 25(5), 378–385 (1995). https://doi.org/10.1007/BF02359594

    Article  Google Scholar 

  7. Modi, S., Bhattacharya, M., Khushu, S.: Neuroimaging in cognitive assessment of armed forces personnel. In: Kaur, G., Awasthy, S., Mandal, M.K. (eds.) Psychometric Testing in Armed Forces: Issues and Challenges, pp. 168–192. Pentagon Press, New Delhi (2012)

    Google Scholar 

  8. Ren, P., Ma, X., Lai, W., et al.: Comparison of the use of blink rate and blink rate variability for mental state recognition. IEEE Trans. Neural Syst. Rehabil. Eng. 27, 867–875 (2019). https://doi.org/10.1109/TNSRE.2019.2906371

    Article  Google Scholar 

  9. Ponomarenko, V.A.: Medical psychological problems of pilot’s performance in a highly maneuvering flight. Aerosp. Environ. Med. 35, 22–26 (2001)

    Google Scholar 

  10. Lytaev, S.A., Dutov, V.B., Kipyatkov, N.Y.: The estimation of neurocognitive indices in conditions of time’s deficiency and psychological loadings. Int. J. Psychophysiol. 69, 300–301 (2008). https://doi.org/10.1016/j.ijpsycho.2008.05.296

    Article  Google Scholar 

  11. Kljuzhev, V.M., Talalaev, A.A., Lisitsky, A.V.: A basic modern problems of the psychophysiological support of the combat capacity of the Russian army. In: Computer and Brain. New Technologies, pp. 182–200, Nauka, Moscow (2005)

    Google Scholar 

  12. Lytaev, S.A., Shostak, V.I.: The significance of emotional processes in man in the mechanisms of analyzing the effect of varying contrast stimulation. Zhurnal Vysshei Nervnoi Deyatelnosti Imeni I.P Pavlova 43(6), 1067–1074 (1993)

    Google Scholar 

  13. Lytaev, S., Aleksandrov, M., Ulitin, A.: Psychophysiological and intraoperative AEPs and SEPs monitoring for perception, attention and cognition. Commun. Comput. Inf. Sci. 713, 229–236 (2017). https://doi.org/10.1007/978-3-319-58750-9_33

    Article  Google Scholar 

  14. Corr, P.J., McNaughton, N.: Neuroscience and approach/avoidance personality traits: a two stage (valuation–motivation) approach. Neurosci. Biobehav. Rev. 36, 2339–2354 (2012). https://doi.org/10.1016/j.neubiorev.2012.09.013

    Article  Google Scholar 

  15. Lytaev, S., Aleksandrov, M., Lytaev, M.: Estimation of emotional processes in regulation of the structural afferentation of varying contrast by means of visual evoked potentials. Advances in Intelligent Systems and Computing, vol. 953, pp. 288–298 (2020). https://doi.org/10.1007/978-3-030-20473-0_28

  16. Lytaev, S., Aleksandrov, M., Popovich, T., Lytaev, M.: Auditory evoked potentials and PET-scan: early and late mechanisms of selective attention. Advances in Intelligent Systems and Computing, vol. 775, pp. 169–178 (2019). https://doi.org/10.1007/978-3-319-94866-9_17

  17. Lytaev, S.A., Belskaya, K.A.: Integration and disintegration of auditory images perception. Lecture Notes in Computer Science, vol. 9183, pp. 470–480 (2015). https://doi.org/10.1007/978-3-319-20816-9_45

  18. Masakowski, Y.R.: Cognition-centric design: implications for system design & decision making. Int. J. Psychophysiol. 69, 143–144 (2008). https://doi.org/10.1016/j.ijpsycho2008.05.352

    Article  Google Scholar 

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Authors and Affiliations

  1. Saint Petersburg Institute for Informatics and Automation, 14th Line, VO, 39, 199178, Saint Petersburg, Russia

    Sergey Lytaev

  2. Saint Petersburg State Pediatric Medical University, Litovskaya. 2, 194100, Saint Petersburg, Russia

    Sergey Lytaev

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  1. Sergey Lytaev
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Correspondence to Sergey Lytaev .

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Editors and Affiliations

  1. Drexel University, Philadelphia, PA, USA

    Hasan Ayaz

  2. National University of Sciences and Tech (NUST), School of Mech and Manufacturing Eng (SMME), Islamabad, Pakistan

    Umer Asgher

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Lytaev, S. (2021). Modeling and Estimation of Physiological, Psychological and Sensory Indicators for Working Capacity. In: Ayaz, H., Asgher, U. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1201. Springer, Cham. https://doi.org/10.1007/978-3-030-51041-1_28

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