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Pilots’ mental workload prediction based on timeline analysis

BACKGROUND: The aircraft cockpit is a highly intensive human-computer interaction system, and its design directly affects flight safety. OBJECTIVE: To optimize the display interface design in complex flight tasks, the present study aimed to propose a dynamic conceptual framework and a timeline task...

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Detalles Bibliográficos
Autores principales: Liu, Chengping, Wanyan, Xiaoru, Xiao, Xu, Zhao, Jingquan, Duan, Ya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369057/
https://www.ncbi.nlm.nih.gov/pubmed/32364153
http://dx.doi.org/10.3233/THC-209021
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author Liu, Chengping
Wanyan, Xiaoru
Xiao, Xu
Zhao, Jingquan
Duan, Ya
author_facet Liu, Chengping
Wanyan, Xiaoru
Xiao, Xu
Zhao, Jingquan
Duan, Ya
author_sort Liu, Chengping
collection PubMed
description BACKGROUND: The aircraft cockpit is a highly intensive human-computer interaction system, and its design directly affects flight safety. OBJECTIVE: To optimize the display interface design in complex flight tasks, the present study aimed to propose a dynamic conceptual framework and a timeline task analysis method for the quantization of the dynamic time effect of mental workload and the influencing factors of task types in the mental workload prediction model. METHODS: The multi-factor mental workload prediction model based on attention resource allocation was integrated to establish the dynamic prediction model of mental workload. The ergonomics simulation experiment was carried out by recording the data on the performance of embedded subtasks, National Aeronautics and Space Administration-Task Load Index (NASA-TLX) subjective evaluation, and eye tracking. RESULTS: The results indicated that the prediction model had a good prediction accuracy and effectiveness under different simulated interfaces and complex tasks, and the real-time monitoring of pilots’ mental workload state was realized. CONCLUSION: In conclusion, the prediction model and the experimental method could be applied to avoid the overload of the pilot throughout the flight phase by optimizing the display interface and adjusting the flight task.
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spelling pubmed-73690572020-07-22 Pilots’ mental workload prediction based on timeline analysis Liu, Chengping Wanyan, Xiaoru Xiao, Xu Zhao, Jingquan Duan, Ya Technol Health Care Research Article BACKGROUND: The aircraft cockpit is a highly intensive human-computer interaction system, and its design directly affects flight safety. OBJECTIVE: To optimize the display interface design in complex flight tasks, the present study aimed to propose a dynamic conceptual framework and a timeline task analysis method for the quantization of the dynamic time effect of mental workload and the influencing factors of task types in the mental workload prediction model. METHODS: The multi-factor mental workload prediction model based on attention resource allocation was integrated to establish the dynamic prediction model of mental workload. The ergonomics simulation experiment was carried out by recording the data on the performance of embedded subtasks, National Aeronautics and Space Administration-Task Load Index (NASA-TLX) subjective evaluation, and eye tracking. RESULTS: The results indicated that the prediction model had a good prediction accuracy and effectiveness under different simulated interfaces and complex tasks, and the real-time monitoring of pilots’ mental workload state was realized. CONCLUSION: In conclusion, the prediction model and the experimental method could be applied to avoid the overload of the pilot throughout the flight phase by optimizing the display interface and adjusting the flight task. IOS Press 2020-06-04 /pmc/articles/PMC7369057/ /pubmed/32364153 http://dx.doi.org/10.3233/THC-209021 Text en © 2020 – IOS Press and the authors. All rights reserved https://creativecommons.org/licenses/by-nc/4.0/ This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0).
spellingShingle Research Article
Liu, Chengping
Wanyan, Xiaoru
Xiao, Xu
Zhao, Jingquan
Duan, Ya
Pilots’ mental workload prediction based on timeline analysis
title Pilots’ mental workload prediction based on timeline analysis
title_full Pilots’ mental workload prediction based on timeline analysis
title_fullStr Pilots’ mental workload prediction based on timeline analysis
title_full_unstemmed Pilots’ mental workload prediction based on timeline analysis
title_short Pilots’ mental workload prediction based on timeline analysis
title_sort pilots’ mental workload prediction based on timeline analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369057/
https://www.ncbi.nlm.nih.gov/pubmed/32364153
http://dx.doi.org/10.3233/THC-209021
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