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Recent Advances in Occupational Health and Ergonomics of Human-Computer Interaction
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Recent Advances in Occupational Health and Ergonomics of Human-Computer Interaction

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (24 March 2023) | Viewed by 3725

Special Issue Editors

Dr. Jiang Shao

E-Mail Website
Guest Editor
School of Architecture & Design, China University of Mining and Technology, Xuzhou 221116, China
Interests: intelligent interaction and digital design; human factor engineering; health equipment research
Dr. Yafeng Niu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Southeast University, Nanjing 211189, China
Interests: human–computer interaction; design ergonomics

Special Issue Information

Dear Colleagues,

We are organizing a Special Issue on “Recent Advances in Occupational Health and Ergonomics of Human–Computer Interaction” in the International Journal of Environmental Research and Public Health, an international, interdisciplinary, academic, peer reviewed, open access journal. Changes in artificial intelligence technologies are leading to a shift in the form of human–computer interaction, and the key to achieving “natural, accurate and safe” human–computer interaction is the integration and collaboration between human and computer intelligence. However, different industries face different challenges in the process of human–computer interaction. Occupational health and safety management should be extended from traditional industrial enterprises to the whole industry, and from traditional occupational disease prevention and control to address work-related diseases and other issues affecting the physical and mental health of workers. This issue therefore aims to provide new insights into the integration and collaboration among users, products, environments, and systems in various industry sectors from an occupational health and ergonomics perspective. This Special Issue aims to safeguard the health and safety of people and systems in all industry sectors and to enhance the wellbeing and equity of the industry. 

This Special Issue will publish high-quality, peer-reviewed papers, with a particular focus on occupational health, ergonomics, and safety management in the context of human–computer interaction. The topics of interest include but are not limited to occupational health and safety, human–computer interaction, safety management, artificial intelligence, human factors and ergonomics, mental health, health risk analysis, safety behavior, and emergency management. For more information, please contact the editor. 

Dr. Jiang Shao
Dr. Yafeng Niu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • occupational health and safety
  • human–computer interaction
  • safety management
  • artificial intelligence
  • human factors and ergonomics
  • mental health
  • health risk analysis
  • safety behavior
  • emergency management

Published Papers (2 papers)

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Research

12 pages, 2048 KiB  
Article
Recognition Mechanism of Dangerous Goods Marks: Evidence from an Event-Related Potential Study
by Qiang Wei, Xinyu Du, Yixin Lin, Guanhua Hou, Siyuan Liu, Hao Fang and Ming Jin
Int. J. Environ. Res. Public Health 2023, 20(6), 5192; https://doi.org/10.3390/ijerph20065192 - 15 Mar 2023
Viewed by 1402
Abstract
Dangerous goods marks are the most effective means of alerting individuals to the potential dangers associated with the transport of dangerous goods. In order to gain a better understanding of how dangerous goods marks convey risk information, the cognitive processing of dangerous goods [...] Read more.
Dangerous goods marks are the most effective means of alerting individuals to the potential dangers associated with the transport of dangerous goods. In order to gain a better understanding of how dangerous goods marks convey risk information, the cognitive processing of dangerous goods marks was examined by measuring event-related potentials (ERPs). We recruited 23 participants, and their ERP data were recorded. We discovered that the dangerous goods marks elicited a larger P200 amplitude and a smaller N300 amplitude, indicating that, compared to other marks, the dangerous goods marks exhibited stronger warning information and drew more attention from the subjects. Simultaneously, dangerous goods marks elicited insufficient emotional arousal in individuals. Therefore, these findings suggest that the designs of dangerous goods marks need to be improved, such as improving the graphic consistency. Changes in ERP patterns can be used to measure the risk perception level of dangerous goods marks, which can be used as an accurate indicator of the effectiveness of warning sign design. In addition, this study provides a theoretical foundation for the cognitive understanding mechanism of dangerous goods marks. Full article
(This article belongs to the Special Issue Recent Advances in Occupational Health and Ergonomics of Human-Computer Interaction)
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19 pages, 1917 KiB  
Article
A Task Complexity Analysis Method to Study the Emergency Situation under Automated Metro System
by Ke Niu, Wenbo Liu, Jia Zhang, Mengxuan Liang, Huimin Li, Yaqiong Zhang and Yihang Du
Int. J. Environ. Res. Public Health 2023, 20(3), 2314; https://doi.org/10.3390/ijerph20032314 - 28 Jan 2023
Viewed by 1419
Abstract
System upgrades and team members interactions lead to changes in task structure. Therefore, in order to handle emergencies efficiently and safely, a comprehensive method of the traffic dispatching team task complexity (TDTTC) is proposed based on team cognitive work analysis (Team-CWA) and network [...] Read more.
System upgrades and team members interactions lead to changes in task structure. Therefore, in order to handle emergencies efficiently and safely, a comprehensive method of the traffic dispatching team task complexity (TDTTC) is proposed based on team cognitive work analysis (Team-CWA) and network feature analysis. The method comes from the perspective of the socio-technical system. Two stages were included in this method. In the first stage, four phases of Team-CWA, i.e., team work domain analysis, team control task analysis, team strategies analysis, and team worker competencies analysis, were applied in the qualitative analysis of TDTTC. Then in the second stage, a mapping process was established based on events and information cues. After the team task network was established, the characteristic indexes of node degree/average degree, average shortest path length, agglomeration coefficient, and overall network performance for TDTTC were extracted to analyze TDTTC quantitatively. The cases of tasks for screen door fault under grade of automation GOA1–GOA4 were compared. The results revealed that the more nodes and communication between nodes, the larger the network scale was, which would lead to the TDTTC being more complicated no matter what level of automation system it was under. This method is not only the exploration of cognitive engineering theory in the field of task complexity, but also the innovation of team task complexity in the development of automatic metro operation. Full article
(This article belongs to the Special Issue Recent Advances in Occupational Health and Ergonomics of Human-Computer Interaction)
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