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Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks

In the main control room (MCR) of a nuclear power plant (NPP), the quality of an operator's performance can depend on their level of attention to the task. Insufficient operator attention accounted for more than 26% of the total causes of human errors and is the highest category for errors. It...

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Autores principales: Kim, Jung Hwan, Kim, Chul Min, Jung, Eun-Soo, Yim, Man-Sung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780753/
https://www.ncbi.nlm.nih.gov/pubmed/33408623
http://dx.doi.org/10.3389/fncom.2020.596531
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author Kim, Jung Hwan
Kim, Chul Min
Jung, Eun-Soo
Yim, Man-Sung
author_facet Kim, Jung Hwan
Kim, Chul Min
Jung, Eun-Soo
Yim, Man-Sung
author_sort Kim, Jung Hwan
collection PubMed
description In the main control room (MCR) of a nuclear power plant (NPP), the quality of an operator's performance can depend on their level of attention to the task. Insufficient operator attention accounted for more than 26% of the total causes of human errors and is the highest category for errors. It is therefore necessary to check whether operators are sufficiently attentive either as supervisors or peers during reactor operation. Recently, digital control technologies have been introduced to the operating environment of an NPP MCR. These upgrades are expected to enhance plant and operator performance. At the same time, because personal computers are used in the advanced MCR, the operators perform more cognitive works than physical work. However, operators may not consciously check fellow operators' attention in this environment indicating potentially higher importance of the role of operator attention. Therefore, remote measurement of an operator's attention in real time would be a useful tool, providing feedback to supervisors. The objective of this study is to investigate the development of quantitative indicators that can identify an operator's attention, to diagnose or detect a lack of operator attention thus preventing potential human errors in advanced MCRs. To establish a robust baseline of operator attention, this study used two of the widely used biosignals: electroencephalography (EEG) and eye movement. We designed an experiment to collect EEG and eye movements of the subjects who were monitoring and diagnosing nuclear operator safety-relevant tasks. There was a statistically significant difference between biosignals with and without appropriate attention. Furthermore, an average classification accuracy of about 90% was obtained by the k-nearest neighbors and support vector machine classifiers with a few EEG and eye movements features. Potential applications of EEG and eye movement measures in monitoring and diagnosis tasks in an NPP MCR are also discussed.
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spelling pubmed-77807532021-01-05 Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks Kim, Jung Hwan Kim, Chul Min Jung, Eun-Soo Yim, Man-Sung Front Comput Neurosci Neuroscience In the main control room (MCR) of a nuclear power plant (NPP), the quality of an operator's performance can depend on their level of attention to the task. Insufficient operator attention accounted for more than 26% of the total causes of human errors and is the highest category for errors. It is therefore necessary to check whether operators are sufficiently attentive either as supervisors or peers during reactor operation. Recently, digital control technologies have been introduced to the operating environment of an NPP MCR. These upgrades are expected to enhance plant and operator performance. At the same time, because personal computers are used in the advanced MCR, the operators perform more cognitive works than physical work. However, operators may not consciously check fellow operators' attention in this environment indicating potentially higher importance of the role of operator attention. Therefore, remote measurement of an operator's attention in real time would be a useful tool, providing feedback to supervisors. The objective of this study is to investigate the development of quantitative indicators that can identify an operator's attention, to diagnose or detect a lack of operator attention thus preventing potential human errors in advanced MCRs. To establish a robust baseline of operator attention, this study used two of the widely used biosignals: electroencephalography (EEG) and eye movement. We designed an experiment to collect EEG and eye movements of the subjects who were monitoring and diagnosing nuclear operator safety-relevant tasks. There was a statistically significant difference between biosignals with and without appropriate attention. Furthermore, an average classification accuracy of about 90% was obtained by the k-nearest neighbors and support vector machine classifiers with a few EEG and eye movements features. Potential applications of EEG and eye movement measures in monitoring and diagnosis tasks in an NPP MCR are also discussed. Frontiers Media S.A. 2020-12-21 /pmc/articles/PMC7780753/ /pubmed/33408623 http://dx.doi.org/10.3389/fncom.2020.596531 Text en Copyright © 2020 Kim, Kim, Jung and Yim. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Kim, Jung Hwan
Kim, Chul Min
Jung, Eun-Soo
Yim, Man-Sung
Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks
title Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks
title_full Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks
title_fullStr Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks
title_full_unstemmed Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks
title_short Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks
title_sort biosignal-based attention monitoring to support nuclear operator safety-relevant tasks
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780753/
https://www.ncbi.nlm.nih.gov/pubmed/33408623
http://dx.doi.org/10.3389/fncom.2020.596531
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