A Bibliometric Analysis of Neuroscience Tools Use in Construction Health and Safety Management.

Zhikun Ding, Zhaoyang Xiong, Yewei Ouyang
Author Information
  1. Zhikun Ding: Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education, Shenzhen 518060, China.
  2. Zhaoyang Xiong: Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518060, China.
  3. Yewei Ouyang: Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.

Abstract

Despite longstanding traditional construction health and safety management (CHSM) methods, the construction industry continues to face persistent challenges in this field. Neuroscience tools offer potential advantages in addressing these safety and health issues by providing objective data to indicate subjects' cognition and behavior. The application of neuroscience tools in the CHSM has received much attention in the construction research community, but comprehensive statistics on the application of neuroscience tools to CHSM is lacking to provide insights for the later scholars. Therefore, this study applied bibliometric analysis to examine the current state of neuroscience tools use in CHSM. The development phases; the most productive journals, regions, and institutions; influential scholars and articles; author collaboration; reference co-citation; and application domains of the tools were identified. It revealed four application domains: monitoring the safety status of construction workers, enhancing the construction hazard recognition ability, reducing work-related musculoskeletal disorders of construction workers, and integrating neuroscience tools with artificial intelligence techniques in enhancing occupational safety and health, where magnetoencephalography (EMG), electroencephalography (EEG), eye-tracking, and electrodermal activity (EDA) are four predominant neuroscience tools. It also shows a growing interest in integrating the neuroscience tools with artificial intelligence techniques to address the safety and health issues. In addition, future studies are suggested to facilitate the applications of these tools in construction workplaces by narrowing the gaps between experimental settings and real situations, enhancing the quality of data collected by neuroscience tools and performance of data processing algorithms, and overcoming user resistance in tools adoption.

Keywords

References

  1. Autom Constr. 2020 Nov;119: [PMID: 33897107]
  2. Database (Oxford). 2011 Jan 18;2011:baq036 [PMID: 21245076]
  3. Front Hum Neurosci. 2019 Mar 19;13:57 [PMID: 30941023]
  4. Front Public Health. 2023 Feb 13;11:1072521 [PMID: 36908460]
  5. Int Arch Occup Environ Health. 2019 Apr;92(3):295-307 [PMID: 30443711]
  6. Scientometrics. 2010 Aug;84(2):523-538 [PMID: 20585380]
  7. Sensors (Basel). 2022 Dec 12;22(24): [PMID: 36560096]
  8. Appl Ergon. 2016 Jan;52:62-8 [PMID: 26360195]
  9. Cochrane Database Syst Rev. 2018 Feb 05;2:CD006251 [PMID: 29400395]
  10. BMC Public Health. 2014 Oct 16;14:1075 [PMID: 25318646]
  11. Ergonomics. 2020 Sep;63(9):1182-1193 [PMID: 32436438]
  12. Front Public Health. 2022 Nov 30;10:993700 [PMID: 36530655]
  13. Neurosci Biobehav Rev. 2014 Jul;44:58-75 [PMID: 23116991]
  14. J Occup Med Toxicol. 2011 Apr 21;6:11 [PMID: 21510851]
  15. J Safety Res. 2017 Jun;61:167-176 [PMID: 28454862]
  16. J Bus Res. 2021 Jan;122:534-566 [PMID: 33012896]
  17. Int J Occup Saf Ergon. 2023 Mar;29(1):207-215 [PMID: 35098890]
  18. BMC Musculoskelet Disord. 2012 Oct 13;13:196 [PMID: 23061990]
  19. Occup Med (Lond). 2015 Apr;65(3):245-50 [PMID: 25701835]
  20. Int J Environ Res Public Health. 2020 Oct 12;17(20): [PMID: 33053832]
  21. Front Neurosci. 2022 Apr 26;16:891725 [PMID: 35557612]
  22. Front Neurosci. 2022 Jun 21;16:895666 [PMID: 35801176]
  23. Hum Factors. 2022 Feb 26;:187208211066666 [PMID: 35225014]
  24. BMC Public Health. 2011 Oct 31;11:836 [PMID: 22040007]
  25. Work. 2018;60(4):661-671 [PMID: 30103367]
  26. Int Arch Occup Environ Health. 2019 Aug;92(6):855-864 [PMID: 30941545]
  27. J Med Internet Res. 2018 Dec 19;20(12):e10272 [PMID: 30567694]
  28. BMC Musculoskelet Disord. 2015 Oct 16;16:302 [PMID: 26474867]
  29. Int J Surg. 2021 Apr;88:105906 [PMID: 33789826]
  30. Int J Environ Res Public Health. 2019 Oct 28;16(21): [PMID: 31661845]
  31. Appl Ergon. 2010 Oct;41(6):822-31 [PMID: 20206915]
  32. Annu Rev Public Health. 1995;16:165-88 [PMID: 7639869]
  33. J Neurosci Methods. 2004 Mar 15;134(1):9-21 [PMID: 15102499]

Grants

  1. 71974132/National Nature Science Foundation of China
  2. JCYJ20190808115809385/Shenzhen Science and Technology Program
  3. 20220810160221001/Shenzhen Science and Technology Program (the Stable Support Plan Program)

MeSH Term

Humans
Artificial Intelligence
Safety Management
Workplace
Bibliometrics
Electroencephalography
Construction Industry

Word Cloud

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