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Application of Cardio-Forecasting for Evaluation of Human—Operator Performance

Author

Listed:
  • Anton Panda

    (Department of Automobile and Manufacturing Technologies, Faculty of Manufacturing Technologies with a Seat in Prešov, Technical University of Kosice, Bayerova 1, 080 01 Prešov, Slovakia)

  • Volodymyr Nahornyi

    (Department of Computer Science, Faculty of Electronics and Information Technologies, Sumy State University, Rimsky-Korsakov, 2, 44007 Sumy, Ukraine)

  • Jan Valíček

    (Department of Electrical Engineering, Faculty of Engineering, Slovak University of Agriculture in Nitra, Automation and Informatics, Trieda Andreja Hlinku 609/2, 949 76 Nitra, Slovakia
    Department of Mechanical Engineering, Faculty of Technology, Institute of Technology and Business in České Budějovice, Okružní 10, 370 01 České Budějovice, Czech Republic)

  • Marta Harničárová

    (Department of Electrical Engineering, Faculty of Engineering, Slovak University of Agriculture in Nitra, Automation and Informatics, Trieda Andreja Hlinku 609/2, 949 76 Nitra, Slovakia
    Department of Mechanical Engineering, Faculty of Technology, Institute of Technology and Business in České Budějovice, Okružní 10, 370 01 České Budějovice, Czech Republic)

  • Iveta Pandová

    (Department of Automobile and Manufacturing Technologies, Faculty of Manufacturing Technologies with a Seat in Prešov, Technical University of Kosice, Bayerova 1, 080 01 Prešov, Slovakia)

  • Cristina Borzan

    (Department of Public Health and Management, Iuliu Hatieganu University of Medicine and Pharmacy, Strada Victor Babeș 8, 400000 Cluj-Napoca, Romania)

  • Samuel Cehelský

    (Department of Automobile and Manufacturing Technologies, Faculty of Manufacturing Technologies with a Seat in Prešov, Technical University of Kosice, Bayerova 1, 080 01 Prešov, Slovakia)

  • Lukáš Androvič

    (Department of Automobile and Manufacturing Technologies, Faculty of Manufacturing Technologies with a Seat in Prešov, Technical University of Kosice, Bayerova 1, 080 01 Prešov, Slovakia)

  • Hakan Tozan

    (Department of Industrial Engineering, School of Engineering and Natural Sciences, Istanbul Medipol University, Kavacik Mh. Ekinciler Cd., 34010 Istanbul, Turkey
    Health Systems and Policies Research Center, Istanbul Medipol University, Kavacik Mh. Ekinciler Cd., 34010 Istanbul, Turkey)

  • Milena Kušnerová

    (Department of Mechanical Engineering, Faculty of Technology, Institute of Technology and Business in České Budějovice, Okružní 10, 370 01 České Budějovice, Czech Republic)

Abstract

The paper presents the results of the development of the cardio-forecasting technology, which introduces a new method to monitor the state of human-operator, which is characteristic for the given production conditions and for individual operators, to predict the moment of exhaustion of his/her working capacity. The work aims to demonstrate the unique, distinctive features of the cardio-forecasting technology for predicting an individual limit of his/her working capacity for each person. A unique methodology for predicting individually for each person the moment when he/she reaches the limit of his/her working capacity is based on a spectral analysis of a human phonocardiogram in order to isolate the frequency component located at the heart contraction frequency. The trend of the amplitude of this component is approximated by its model; consequently, the coefficients of the trend model are determined. They include the operator’s operating time until his/her working capacity is exhausted. A methodology for predicting the moment when he/she reaches the limit of his/her working capacity for each person individually and assessment based on this degree of criticality of their condition will be realized as a software application for smartphones using the Android operating system.

Suggested Citation

  • Anton Panda & Volodymyr Nahornyi & Jan Valíček & Marta Harničárová & Iveta Pandová & Cristina Borzan & Samuel Cehelský & Lukáš Androvič & Hakan Tozan & Milena Kušnerová, 2020. "Application of Cardio-Forecasting for Evaluation of Human—Operator Performance," IJERPH, MDPI, vol. 17(1), pages 1-12, January.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:1:p:326-:d:304574
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    References listed on IDEAS

    as
    1. Marit Skogstad & Asgeir Mamen & Lars-Kristian Lunde & Bente Ulvestad & Dagfinn Matre & Hans Christian D. Aass & Reidun Øvstebø & Pia Nielsen & Kari N. Samuelsen & Øivind Skare & Per Anton Sirnes, 2019. "Shift Work Including Night Work and Long Working Hours in Industrial Plants Increases the Risk of Atherosclerosis," IJERPH, MDPI, vol. 16(3), pages 1-11, February.
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