Exploring the utility of robots in exposure studies

• Published in: Journal of exposure science & environmental epidemiology Vol. 31; no. 4; pp. 784 - 794
• Main Authors: Feld-Cook, Elisabeth, Shome, Rahul, Zaleski, Rosemary T., Mohan, Krishnan, Kourtev, Hristiyan, Bekris, Kostas E., Weisel, Clifford P., Shin, Jennifer (Mi K.)
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.07.2021; Nature Publishing Group
• Subjects: Data entry; Dose-response relationship (Biochemistry); Drywall; Environment; Epidemiology; Estimates; Exposure; Human subjects; Humanoid; Medical research; Medicine; Medicine & Public Health; Medicine, Experimental; Methods; Organic compounds; Product development; Research ethics; Robots; Technology application; VOCs; Volatile organic compounds; United States; Volatile organic compounds; Personal exposure; Exposure modeling; Robots
• ISSN: 1559-0631; 1559-064X
• DOI: 10.1038/s41370-019-0190-x

Obtaining valid, reliable quantitative exposure data can be a significant challenge for industrial hygienists, exposure scientists, and other health science professionals. In this proof-of-concept study, a robotic platform was programmed to perform a simple task as a plausible alternative to human subjects in exposure studies for generating exposure data. The use of robots offers several advantages over the use of humans. Research can be completed more efficiently and there is no need to recruit, screen, or train volunteers. In addition, robots can perform tasks repeatedly without getting tired allowing for collection of an unlimited number of measurements using different chemicals to assess exposure impacts from formulation changes and new product development. The use of robots also eliminates concerns with intentional human exposures while removing health research ethics review requirements which are time consuming. In this study, a humanoid robot was programmed to paint drywall, while volatile organic compounds were measured in air for comparison to model estimates. The measured air concentrations generally agreed with more advanced exposure model estimates. These findings suggest that robots have potential as a methodology for generating exposure measurements relevant to human activities, but without using human subjects.