Literature DB >> 23654299

Mental workload measurement for emergency operating procedures in digital nuclear power plants.

Qin Gao1, Yang Wang, Fei Song, Zhizhong Li, Xiaolu Dong.   

Abstract

Mental workload is a major consideration for the design of emergency operation procedures (EOPs) in nuclear power plants. Continuous and objective measures are desired. This paper compares seven mental workload measurement methods (pupil size, blink rate, blink duration, heart rate variability, parasympathetic/sympathetic ratio, total power and (Goals, Operations, Methods, and Section Rules)-(Keystroke Level Model) GOMS-KLM-based workload index) with regard to sensitivity, validity and intrusiveness. Eighteen participants performed two computerised EOPs of different complexity levels, and mental workload measures were collected during the experiment. The results show that the blink rate is sensitive to both the difference in the overall task complexity and changes in peak complexity within EOPs, that the error rate is sensitive to the level of arousal and correlate to the step error rate and that blink duration increases over the task period in both low and high complexity EOPs. Cardiac measures were able to distinguish tasks with different overall complexity. The intrusiveness of the physiological instruments is acceptable. Finally, the six physiological measures were integrated using group method of data handling to predict perceived overall mental workload. PRACTITIONER
SUMMARY: The study compared seven measures for evaluating the mental workload with emergency operation procedure in nuclear power plants. An experiment with simulated procedures was carried out, and the results show that eye response measures are useful for assessing temporal changes of workload whereas cardiac measures are useful for evaluating the overall workload.

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Mesh:

Year:  2013        PMID: 23654299     DOI: 10.1080/00140139.2013.790483

Source DB:  PubMed          Journal:  Ergonomics        ISSN: 0014-0139            Impact factor:   2.778


  9 in total

1.  Assessment of mental workload based on multi-physiological signals.

Authors:  Xiaoli Fan; Chaoyi Zhao; Xin Zhang; Hong Luo; Wei Zhang
Journal:  Technol Health Care       Date:  2020       Impact factor: 1.285

2.  Experienced mental workload, perception of usability, their interaction and impact on task performance.

Authors:  Luca Longo
Journal:  PLoS One       Date:  2018-08-01       Impact factor: 3.240

3.  A Systematic Review of Physiological Measures of Mental Workload.

Authors:  Da Tao; Haibo Tan; Hailiang Wang; Xu Zhang; Xingda Qu; Tingru Zhang
Journal:  Int J Environ Res Public Health       Date:  2019-07-30       Impact factor: 3.390

4.  Desktop lighting for comfortable use of a computer screen.

Authors:  Lu Han; Hechen Zhang; Zhongxia Xiang; Jinze Shang; Shabila Anjani; Yu Song; Peter Vink
Journal:  Work       Date:  2021

5.  Effects of Noise Exposure and Mental Workload on Physiological Responses during Task Execution.

Authors:  Yurong Fan; Jin Liang; Xiaodong Cao; Liping Pang; Jie Zhang
Journal:  Int J Environ Res Public Health       Date:  2022-09-29       Impact factor: 4.614

Review 6.  Application of Eye Tracking Technology in Aviation, Maritime, and Construction Industries: A Systematic Review.

Authors:  Daniel Martinez-Marquez; Sravan Pingali; Kriengsak Panuwatwanich; Rodney A Stewart; Sherif Mohamed
Journal:  Sensors (Basel)       Date:  2021-06-23       Impact factor: 3.576

7.  A comprehensive prediction and evaluation method of pilot workload.

Authors:  Chuanyan Feng; Xiaoru Wanyan; Kun Yang; Damin Zhuang; Xu Wu
Journal:  Technol Health Care       Date:  2018       Impact factor: 1.285

8.  A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems.

Authors:  Mario Amrehn; Stefan Steidl; Reinier Kortekaas; Maddalena Strumia; Markus Weingarten; Markus Kowarschik; Andreas Maier
Journal:  Int J Biomed Imaging       Date:  2019-09-05

9.  Cardiovascular Biomarkers' Inherent Timescales in Mental Workload Assessment During Simulated Air Traffic Control Tasks.

Authors:  Thea Radüntz; Thorsten Mühlhausen; Marion Freyer; Norbert Fürstenau; Beate Meffert
Journal:  Appl Psychophysiol Biofeedback       Date:  2020-10-04
  9 in total

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