A mental workload predicator model for the design of pre alarm systems

  • Authors:

  • Sheue-Ling Hwang;Yi-Jan Yau;Yu-Ting Lin;Jun Hao Chen;Tsun-Hung Huang;Tzu-Chung Yenn;Chong-Cheng Hsu

  • Affiliations:

  • Institute of Industrial Engineering & Engineering Management, National Tsing Hua University, Hsinchu, Taiwan, R.O.C;Institute of Industrial Engineering & Engineering Management, National Tsing Hua University, Hsinchu, Taiwan, R.O.C;Institute of Industrial Engineering & Engineering Management, National Tsing Hua University, Hsinchu, Taiwan, R.O.C;Institute of Industrial Engineering & Engineering Management, National Tsing Hua University, Hsinchu, Taiwan, R.O.C;Institute of Industrial Engineering & Engineering Management, National Tsing Hua University, Hsinchu, Taiwan, R.O.C and Department of Industrial Engineering and Management, National Chin-Yi Instit ...;Institute of Nuclear Energy Research, Lungtan, Taiwan, R.O.C;Department of Industrial Engineering and Management, National Chin-Yi Institute of Technology, Taichung, Taiwan, R.O.C

  • Venue:
  • EPCE'07 Proceedings of the 7th international conference on Engineering psychology and cognitive ergonomics
  • Year:
  • 2007

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Abstract

This study investigated the operator's mental workload of the fourth Nuclear Power Plant in Taiwan. An experiment including the primary and secondary tasks was designed to simulate the reactor shutdown procedure of the Nuclear Power Plant. The performance of secondary task, the subjective mental workload and seven physiological signals of participant were measured. The Group Method of Data Handling (GMDH) was applied to integrate these physiological signals to develop a mental workload predictive model. The relationship between subject mental workload and the performance of secondary task is highly correlated with Pearson correlation coefficient as 0.691. The validity of the proposed model is very high with R2=0.85. The proposed model is expected to provide supervisor a reference value of operator's performance by giving physiological signals. Besides nuclear power plant, the proposed model could be applied to other fields such as aviation, air transportation control, driving and radar vigilance, etc.