{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T02:13:22Z","timestamp":1783995202086,"version":"3.55.0"},"reference-count":113,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["71974132"],"award-info":[{"award-number":["71974132"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["JCYJ20190808115809385"],"award-info":[{"award-number":["JCYJ20190808115809385"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["20220810160221001"],"award-info":[{"award-number":["20220810160221001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Program","award":["71974132"],"award-info":[{"award-number":["71974132"]}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20190808115809385"],"award-info":[{"award-number":["JCYJ20190808115809385"]}]},{"name":"Shenzhen Science and Technology Program","award":["20220810160221001"],"award-info":[{"award-number":["20220810160221001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2019 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.<\/jats:p>","DOI":"10.3390\/s23239522","type":"journal-article","created":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T09:37:54Z","timestamp":1701337074000},"page":"9522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["A Bibliometric Analysis of Neuroscience Tools Use in Construction Health and Safety Management"],"prefix":"10.3390","volume":"23","author":[{"given":"Zhikun","family":"Ding","sequence":"first","affiliation":[{"name":"Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education, Shenzhen 518060, China"},{"name":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518060, China"},{"name":"Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University, Shenzhen 518060, China"},{"name":"Shenzhen Key Laboratory of Green, Efficient and Intelligent Construction of Underground Metro Station, Shenzhen University, Shenzhen 518060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoyang","family":"Xiong","sequence":"additional","affiliation":[{"name":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518060, China"},{"name":"Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University, Shenzhen 518060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yewei","family":"Ouyang","sequence":"additional","affiliation":[{"name":"Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"105457","DOI":"10.1016\/j.ssci.2021.105457","article-title":"Occupational Accident Analysis According to Professionals of Different Construction Phases Using Association Rules","volume":"144","author":"Cabello","year":"2021","journal-title":"Saf. 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