Exploring the utility of robots in exposure studies.

Journal: Journal of exposure science & environmental epidemiology
Published Date:

Abstract

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.

Authors

  • Elisabeth Feld-Cook
    Environmental and Occupational Health Sciences Institute, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
  • Rahul Shome
    PRACSYS Lab, Department of Computer Science, School of Arts and Sciences at Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
  • Rosemary T Zaleski
    ExxonMobil Biomedical Sciences Inc., Annandale, NJ, 08801, USA.
  • Krishnan Mohan
    Environmental and Occupational Health Sciences Institute, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
  • Hristiyan Kourtev
    PRACSYS Lab, Department of Computer Science, School of Arts and Sciences at Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
  • Kostas E Bekris
    PRACSYS Lab, Department of Computer Science, School of Arts and Sciences at Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
  • Clifford P Weisel
    Environmental and Occupational Health Sciences Institute, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
  • Jennifer Mi K Shin
    ExxonMobil Biomedical Sciences Inc., Spring, TX, 77389, USA. jennifer.shin@exxonmobil.com.