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ERP Study of Mine Management System Warning Interface under Fatigue

Author

Listed:
  • Yuxin Bai

    (School of Architecture & Design, China University of Mining and Technology, Xuzhou 221116, China)

  • Jiang Shao

    (School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Ying Zhang

    (School of Architecture & Design, China University of Mining and Technology, Xuzhou 221116, China)

  • Lulu Chen

    (School of Architecture & Design, China University of Mining and Technology, Xuzhou 221116, China)

  • Xijie Zhao

    (School of Architecture & Design, China University of Mining and Technology, Xuzhou 221116, China)

  • Fangyuan Tian

    (School of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Chengqi Xue

    (School of Mechanical Engineering, Southeast University, Nanjing 211189, China)

Abstract

Due to the large volume of monitoring data in mines, concentrating on and reviewing the data for a long period of time will easily cause fatigue. To study the influence of different visual codes of early-warning interfaces on the response of individuals who are fatigued, the changes in the subjective fatigue and corresponding frequency waves are compared before and after a fatigue-inducing task, as well as using event-related potential to study the behavioral data and EEG signals of subjects who participated in an oddball task on an early-warning interface. The results showed that all 14 subjects became fatigued after the fatigue-inducing task, and the amplitude of P200 when text is used in a fatigued state was the largest, with the longest latency. The subjects showed a slower reaction time and a reduced accuracy rate, thus indicating that in designing a warning interface, when text rather than color is used as a visual code, the operating load will be larger, mental load is increased, and attention resources are consumed. The experimental results provide the basis for the design and evaluation of early-warning interfaces of mine management systems.

Suggested Citation

  • Yuxin Bai & Jiang Shao & Ying Zhang & Lulu Chen & Xijie Zhao & Fangyuan Tian & Chengqi Xue, 2022. "ERP Study of Mine Management System Warning Interface under Fatigue," IJERPH, MDPI, vol. 19(19), pages 1-14, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12616-:d:932206
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    References listed on IDEAS

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    1. Josephine Singo & John Bosco Isunju & Dingani Moyo & Stephan Bose-O’Reilly & Nadine Steckling-Muschack & Antony Mamuse, 2022. "Accidents, Injuries, and Safety among Artisanal and Small-Scale Gold Miners in Zimbabwe," IJERPH, MDPI, vol. 19(14), pages 1-21, July.
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