The use of non-invasive measures to predict thermal strain: How accurate are universal models?

Over the past few decades there has been an upsurge in the development of monitoring devices that estimate levels of thermal strain non-invasively. However, developing a non-invasive monitoring device that estimates body core temperature (Tc) with a certain level of accuracy that is satisfactory over multiple heat stress scenarios and a wide range of body core temperatures has been shown to be a difficult task [1]. The aim of this study was to investigate the potential of using a combination of simple non-invasive measures to estimate rectal temperature (Tre) (used as a reference for Tc) over multiple types of heat stress scenarios within a varied population

Insulated skin temperature as a measure of core body temperature for individuals wearing CBRN protective clothing

This study assessed the validity of insulated skin temperature (Tis) to predict rectal temperature (Tre) for use as a non-invasive measurement of thermal strain to reduce the risk of heat illness for emergency service personnel. Volunteers from the Police, Fire and Rescue, and Ambulance Services performed rolerelated tasks in hot (30 ◦C) and neutral (18 ◦C) conditions, wearing service specific personal protective equipment. Insulated skin temperature and micro climate temperature (Tmc) predicted Tre with an adjusted r2 = 0.87 and standard error of the estimate (SEE) of 0.19 ◦C. A bootstrap validation of the equation resulted in an adjusted r2 = 0.85 and SEE = 0.20 ◦C. Taking into account the 0.20 ◦C error, the prediction of Tre resulted in a sensitivity and specificity of 100% and 91%, respectively. Insulated skin temperature and Tmc can be used in a model to predict Tre in emergency service personnel wearing CBRN protective clothing with an SEE of 0.2 ◦C. However, the model is only valid for Tis over 36.5 ◦C, above which thermal stability is reached between the core and the skin

Monitoring heat strain in physically challenging environments

Individuals working in physically demanding occupations can experience high levels of heat strain due to the physical demands of the job, harsh environmental conditions and/or the wearing of personnel protective equipment (PPE). The ability to monitor body core temperature (Tc) could reduce the risk of heat illness. The main purpose of this thesis was to examine non-invasive methods of Tc measurement. Studies 1, 2 and 3 investigated the validity of insulated skin temperature (Tis) as a non-invasive measure of Tc, in emergency service (ES) and military personnel. In Study 1, a model including Tis and micro-climate temperature (Tmc) was developed to predict rectal temperature (Tre) for ES personnel wearing PPE. The resulting standard error of the estimate (SEE=0.20 °C) was within the a-priori pre-defined SEE limit (0.20 °C), providing encouragement for the further investigation of Tis as a surrogate measure of Tc. Studies 2 and 3 sought to determine the validity of Tis in predicting Tre in military personnel, wearing PPE in temperate conditions (Study 2) and in a desert environment (Study 3). Although the SEE was outside the acceptable SEE in Study 2 (0.22 °C), the sensitivity (97 %) for predicting Tre values over 38.5 °C provided scope for a military application for Tis to predict Tc. In Study 3, Tis could not predict Tre in a desert environment, with simulated solar radiation directly affecting Tis and invalidating the prediction (SEE = 0.29 °C). Study 4 involved a series of experiments performed under six conditions in a thermal chamber with two clothing types, to determine whether the addition of other physiological and/or environmental factors might improve the prediction of Tre. A model including Tis and Tmc resulted in an SEE of 0.26 °C; with heart rate (HR) and work significantly reducing the SEE (0.23 °C) (p<0.05). Although the SEE achieved in the validation (0.27 °C) was larger than in Studies 1 and 2, these results provide novel information regarding the measures that explain the variance when predicting Tre in a wide range of heat stress conditions. To our knowledge this is the most detailed analysis of Tc prediction based on non-invasive sensors, with the inclusion of all the parameters that are likely to be relevant. The main conclusion from the work thus far was that it is unlikely a reliable prediction of Tc can be achieved, using Tis, for validity under different types of heat stress conditions. However, predictions of Tre for more specific conditions using Tis are achievable. Having collected a vast amount of data on participants demonstrating high levels of heat strain, it was considered valuable to analyse the drop-outs in more detail. More specifically the goal of Study 5 was to see whether measurements of individual heat strain (Tc, HR) and the combination of these in the Physiological Strain Index (PSI) had predictive power for individual drop-out. There were no differences in PSI between individuals who stopped from heat exhaustion (HE) (7.9 ± 0.8) and those who completed the trial (C) (8.3 ± 0.9). The only differences between these two groups were rate of rise of Tre, (C 0.03 ± 0.01 °C min-1 and; HE 0.04 ± 0.01 °C min-1), chest temperature (Tchest) (C 38.1 ± 1.0 °C and; HE 39.0 ± 0.6 °C) and the temperature gradient between Tchest and Tre (C 1.04 ± 1.07 °C, and; HE -0.05 ± 0.59 °C) (p<0.05); It was therefore concluded that PSI did not provide a good personal heat strain measure that would predict tolerance of the individual. In conclusion, Tis (with Tmc) is promising as a non-invasive measure of Tre, in ES and military personnel wearing fully-encapsulated PPE, based on the resulting SEE and sensitivity and specificity. With the current methodology, it is not valid in conditions with a solar load. The addition of HR and work together improve the prediction of Tre. The PSI does not enable identification of individuals who are approaching heat exhaustion, requiring the inclusion of other physiological responses which determine tolerance

<b>Dataset for 'Prediction of Core Body Temperature from Multiple Variables'</b> and '<b>The physiological strain index does not reliably identify individuals at risk of reaching a thermal tolerance limit</b><b>' PROSPIE project</b>

These are datafiles for two papers. The first tried to develop prediction equations for body core temperature based on non-invasive measurement. The second analyses the PSI, the Physiological Strain Index, and evaluates whether this has predictive power for people dropping out from work in the heat.Below the abstracts of the two papers:Prediction of Core Body Temperature from Multiple VariablesThis paper aims to improve the prediction of rectal temperature (Tre) from insulated skin temperature (Tis) and micro-climate temperature (Tmc) previously reported (Richmond et al., Insulated skin temperature as a measure of core body temperature for individuals wearing CBRN protective clothing. Physiol Meas 2013; 34:1531–43.) using additional physiological and/or environmental variables, under several clothing and climatic conditions. Twelve male (25.8±5.1 years; 73.6±11.5kg; 178±6cm) and nine female (24.2±5.1 years; 62.4±11.5kg; 169±3cm) volunteers completed six trials, each consisting of two 40-min periods of treadmill walking separated by a 20-min rest, wearing permeable or impermeable clothing, under neutral (25°C, 50%), moderate (35°C, 35%), and hot (40°C, 25%) conditions, with and without solar radiation (600W m−2). Participants were measured for heart rate (HR) (Polar, Finland), skin temperature (Ts) at 11 sites, Tis (Grant, Cambridge, UK), and breathing rate (f) (Hidalgo, Cambridge, UK). Tmc and relative humidity were measured within the clothing. Tre was monitored as the ‘gold standard’ measure of Tc for industrial or military applications using a 10cm flexible probe (Grant, Cambridge, UK). A stepwise multiple regression analysis was run to determine which of 30 variables (Tis, Ts at 11 sites, HR, f, Tmc, temperature, and humidity inside the clothing front and back, body mass, age, body fat, sex, clothing, Thermal comfort, sensation and perception, and sweat rate) were the strongest on which to base the model. Using a bootstrap methodology to develop the equation, the best model in terms of practicality and validity included Tis, Tmc, HR, and ‘work’ (0 = rest; 1 = exercise), predicting Tre with a standard error of the estimate of 0.27°C and adjusted r2 of 0.86. The sensitivity and specificity for predicting individuals who reached 39°C was 97 and 85%, respectively. Insulated skin temperature was the most important individual parameter for the prediction of Tre. This paper provides novel information about the viability of predicting Tc under a wide range of conditions, using predictors which can practically be measured in a field environment.The physiological strain index does not reliably identify individuals at risk of reaching a thermal tolerance limitPurposeThe physiological strain index (PSI) was developed to assess individuals’ heat strain, yet evidence supporting its use to identify individuals at potential risk of reaching a thermal tolerance limit (TTL) is limited. The aim of this study was to assess whether PSI can identify individuals at risk of reaching a TTL.MethodsFifteen females and 21 males undertook a total of 136 trials, each consisting of two 40–60 minute periods of treadmill walking separated by ~ 15 minutes rest, wearing permeable or impermeable clothing, in a range of climatic conditions. Heart rate (HR), skin temperature (Tsk), rectal temperature (Tre), temperature sensation (TS) and thermal comfort (TC) were measured throughout. Various forms of the PSI-index were assessed including the original PSI, PSIfixed, adaptive-PSI (aPSI) and a version comprised of a measure of heat storage (PSIHS). Final physiological and PSI values and their rate of change (ROC) over a trial and in the last 10 minutes of a trial were compared between trials completed (C, 101 trials) and those terminated prematurely (TTL, 35 trials).ResultsFinal PSIoriginal, PSIfixed, aPSI, PSIHS did not differ between TTL and C (p > 0.05). However, differences between TTL and C occurred in final Tsk, Tre–Tsk, TS, TC and ROC in PSIfixed, Tre, Tsk and HR (p < 0.05).ConclusionThese results suggest the PSI, in the various forms, does not reliably identify individuals at imminent risk of reaching their TTL and its validity as a physiological safety index is therefore questionable. However, a physiological-perceptual strain index may provide a more valid measure.</p