Real-time core body temperature estimation from heart rate for first responders wearing different levels of personal protective equipment

Ergonomics. 2015;58(11):1830-41. doi: 10.1080/00140139.2015.1036792. Epub 2015 May 13.


First responders often wear personal protective equipment (PPE) for protection from on-the-job hazards. While PPE ensembles offer individuals protection, they limit one's ability to thermoregulate, and can place the wearer in danger of heat exhaustion and higher cardiac stress. Automatically monitoring thermal-work strain is one means to manage these risks, but measuring core body temperature (Tc) has proved problematic. An algorithm that estimates Tc from sequential measures of heart rate (HR) was compared to the observed Tc from 27 US soldiers participating in three different chemical/biological training events (45-90 min duration) while wearing PPE. Hotter participants (higher Tc) averaged (HRs) of 140 bpm and reached Tc around 39 °C. Overall the algorithm had a small bias (0.02 °C) and root mean square error (0.21 °C). Limits of agreement (LoA ± 0.48 °C) were similar to comparisons of Tc measured by oesophageal and rectal probes. The algorithm shows promise for use in real-time monitoring of encapsulated first responders.

Practitioner summary: An algorithm to estimate core temperature (Tc) from non-invasive measures of HR was validated. Three independent studies (n = 27) compared the estimated Tc to the observed Tc in humans participating in chemical/ biological hazard training. The algorithm’s bias and variance to observed data were similar to that found from comparisons of oesophageal and rectal measurements.

Keywords: core temperature prediction; fire-fighter monitoring; heat strain; non-invasive; thermal–work strain.

MeSH terms

  • Adult
  • Algorithms*
  • Body Temperature Regulation
  • Body Temperature*
  • Emergency Responders*
  • Female
  • Heart Rate*
  • Hot Temperature
  • Humans
  • Male
  • Military Personnel*
  • Personal Protective Equipment*
  • Physical Exertion
  • Regression Analysis
  • Simulation Training
  • Young Adult