Validity of Heart Rate Derived Core Temperature Estimation During Simulated Firefighting Tasks

doi:10.21203/rs.3.rs-3429078/v1

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Validity of Heart Rate Derived Core Temperature Estimation During Simulated Firefighting Tasks

https://doi.org/10.21203/rs.3.rs-3429078/v1

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Rectal core temperature monitoring can mitigate heat injury but can be invasive and impractical. EQ02 + LifeMonitor is a less invasive estimation of core temperature. Therefore, the primary purpose of this study was to determine the validity of the EQ02 + LifeMonitor validity compared to rectal thermometer core temperatures. Thirteen participants completed simulated firefighting tasks with and without turn out gear, involving four rounds of a 5-minute walk on a treadmill at 2.8 mph/2.5% grade and 20 deadlifts over five minutes in heat [40.6°C; 50% humidity]. During each trial participants wore both an EQ02 + LifeMonitor and DataTherm II rectal thermometer. Devices were statistically equivalent [Δ_upper p < 0.001, Δ_lower p < 0.001] yet there was a statistically significant difference in the value (~ 0.1°C; p < 0.001).There was a significant effect of devices [p < 0.001] and time [p < 0.001], but no interaction effect [p = 0.70] on core temperature drift. Estimated core temperature was marginally different from the DataTherm II and on average overestimated core temperature. These results suggest the EQ02 + LifeMonitor may be a viable, less invasive alternative of assessing core temperature compared to rectal temperature monitoring, especially during rigorous, intermittent activities.

Wearable Technology

Physiological Monitoring

Heat Stress Monitoring

Occupational Physiology

Environmental Physiology

Tactical Athletes

Firefighters are frequently exposed to heat stress. A recent study indicates ~ 75% of firefighters have experienced heat-injury related symptoms with 5% experiencing these symptoms more than 20 times in a year [1]. Firefighter research often involves the use of heated environments [2, 3] and high levels of activity due to required occupational demands [4–9]. The required personal protective equipment (PPE), while life protecting, further increases exposure to heat and exertional stress due to its insulative properties [1, 10–13]. Research has shown firefighters in these environments experience core temperature increases to 39°C or greater [13] and heat related injury can occur as core body temperature approaches 40°C [1]. Thus, real time assessments of core temperature remain vital in firefighter workload monitoring and heat related injury research [14].

The current standard of core temperature assessment in scientific research and emergency medical settings involves using a rectal thermometer [15–17]. Other methods include gastrointestinal pills, tympanic temperatures, and esophageal temperatures [18]. However, these methods are highly invasive or often impractical for daily field usage [19]. Recent efforts to develop non-invasive core temperature monitoring systems include the Equivital EQ02 + LifeMonitor and Black Ghost software, referred to herein as Equivital. This system is comprised of a physiological monitoring strap and validated heart rate-based algorithm to obtain an estimated core temperature [20–22]. The initial validation of the algorithm was completed with a fairly homogenous sample of healthy young US military volunteers in live-field environments to generate the core temperature estimate model [21]. Subsequent studies validating the model in both controlled and live-field environments; involving activities such as, treadmill and cycling exercise or ruck marching. These activities are generally classified as continuous steady state exercise [23]. However, firefighting requires repeated stop-and-go type activities [24]. Previous validation attempts suggest that the estimated core temperature provided by the Equivital was not a viable option for monitoring core temperature during live fire training activities when compared to ingestible thermometer pills [25]. However, while ingestible pills are an accepted tool for in-the-field core temperature monitoring, rectal temperature monitoring remains the gold standard in core temperature monitoring. This presents a potential flaw in validating the Equivital system as the Lin’s Concordance Correlation Coefficient test is intended to validate an experimental measure to the gold-standard [24].

Therefore, the primary aim of this study was to assess the validity of a heart rate derived estimation of core temperature compared to rectal thermometer temperatures during simulated firefighting tasks. We hypothesized that there will be high agreement between the rectal temperature measures and Equivital estimates and will assess this using two one sided t tests as our equivalence test between the devices. A secondary aim we sought to investigate were potential discrepancies in core temperature drift between continuous rectal temperature measures and the Equivital core temperature estimates. Our hypothesis is that we will observe differences in temperature drift trajectories between the rectal core temperature measurement and Equivital estimated core temperature through the continuous exercise task. We will assess this as average core temperature from each device over five-minute epochs. We also aimed to elucidate the impact of turnout gear on physiological strain (core temperature, heart rate, ventilatory rate, and skin temperature responses), and rate of perceived exertion (RPE) experienced during experimental bouts of simulated occupational activities. We hypothesized that turnout gear will significantly increase physiological strain and significantly increase ratings of perceived exertion. Finally, as an exploratory aim, we set out to use area under the curve (AUC) as a potential, novel, method of quantifying heat stress with respect to both changes in core body temperature and time of exposure. To assess this, we will compare the differences in AUC heat stress from paired recreation clothing and firefighter turnout gear exercise trials as measured by the gold-standard rectal core temperature monitoring.

2.1 Participants

A total of 13 participants, eight males and five females, were recruited for this study. All participants were individuals from the local community and met the following inclusion criteria: 19–45 years old and comfortable and familiar carrying out exercise tasks while in an environmental chamber. These criteria were in place to closely match our target population of firefighters while ensuring foundations of fitness were met for the required simulated tasks. Exclusion criteria included: a known medical condition preventing their participation in exercise or requiring medically supervised exercise, currently rehabilitating from recent musculoskeletal injury, currently taking anticoagulants, a history of a heart condition or high blood pressure, angina during exercise, recent heat related injury or orthopedic injury, or currently pregnant. A health history questionnaire and informed consent was completed prior to their engagement in any research activity. All study protocols were approved by the Institutional Review Board of XXX (protocol code #22–149).

2.2 Research design

This was a randomized cross-over design study where participants completed simulated firefighter tasks in an environmental chamber on two separate occasions. Visits were identical with the exception of clothing condition [i.e., recreational exercise clothes (t-shirt and shorts) vs the addition of firefighter turn out gear (bunker jacket and pants)]. Block randomization was generated in Microsoft® Excel (Microsoft Corporations, Redmond, WA). A 7-day wash-out period was included between trials to reduce the risk of residual fatigue impacting subsequent trial performance.

2.3 Experimental Trials

Baseline measurements including blood pressure, height, weight, and hydration status were assessed prior to completing the simulated firefighter tasks (SFT). Participants were then fitted with an Equivital EQ02 + LifeMonitor (Hidalgo, Cambridge, UK) and a DataTherm® II Temperature Monitor 2M Probe Sensor (RG Medical Diagnostics, Wixom, MI, USA) to collect physiological responses during SFT. The Equivitial Black Ghost software estimated core temperature during the SFT (Hidalgo, Cambridge, UK). SFT were conducted in an environmental chamber (ESPEC North America, Inc., Hudsonville, MI, USA) during both conditions to control the temperature and humidity at a constant setting of 40.6°C (105°F) and 50% relative humidity. The temperature was chosen to replicate non-fireground activities such as salvage, highway extractions, and other hot summer emergency responses [26–28]. Measurements were monitored throughout testing to assure a consistent temperature and humidity was maintained during trials. Participants were asked to maintain consistent dietary and exercise habits throughout the study. Participants provided a urine sample to ensure adequate hydration prior to each trial for via urine specific gravity (USG) by portable refractometer (V-Resourcing, Hunan, China). Adequate hydration was defined as a USG value less than 1.025 based on the standard set by the National Athletic Trainers’ Association [29]. Additionally, participants were asked to refrain from caffeine, alcohol, and vigorous exercise the day of the trials.

2.3.1 Simulated Firefighting Tasks (SFT)

The SFT included five minutes of deadlifts (one repetition every 15 seconds) with 40% of participants’ body weight, followed by five minutes of treadmill walking set at 4.5 kph and 2.5% grade. This process was repeated for a total of four rounds (40 minutes of exercise). Intensities were chosen based on discussion with leadership of the local fire departments and reported average physical demands required by firefighters as established by previous research and the National Fire Protection Association (NFPA) [5, 30]. Termination criteria included: the participants reaching volitional fatigue or a rectal core temperature of 39.4°C. If participants reached 38.9°C, exercise was terminated, and the participant remained in the chamber for the remainder of the prescribed time. If core temperature continued to rise and reached 39.4°C participants were removed from the chamber immediately. This termination criteria was set to reduce the risk of exertional heat illness which typically occurs at temperatures > 40°C [31].

2.3.2 Physiological Strain Measures

Variables acquired by the Equivital included heart rate, respiratory rate, skin temperature, and estimated core temperature. However, as respiratory rate is specifically a measure of gas exchange, we will herein be referring to this measure as ventilatory rate because the Equivital is an estimation of mechanical inspiration and expiration (breathes/minutes). Skin temperature was measured at the torso by the Equivital and is measured by an infrared temperature sensor on the back of the Equivital device in contact with the individual’s skin, under the individual's arm (at the mid-axillary line of the thorax in line with individual’s xiphoid process of the sternum). Skin temperature was recorded every minute during SFT. Core temperature was monitored continuously by a DataTherm® II Temperature Monitor 2M Probe Sensor (RG Medical Diagnostics, Wixom, MI, USA). The DataTherm rectal thermometer was inserted approximately 15 cm into the rectal cavity by the participant. This depth was chosen based on previous research that determined this depth provides the best measure of rectal core temperature [32]. The rectal thermometer was permanently marked at 15 cm for participants to assure they inserted to the correct length. Participants then secured the remainder of the rectal thermometer with adhesive tape to fixate the device in order to reduce movement of the probe during the protocol. For confirmation, participants were asked if the thermometer had been inserted to the marked line prior to visit continuation. After assurance of probe insertion length, participants entered the heat chamber to complete SFT. Rate of perceived exertion (RPE) was assessed every five minutes utilizing the Borg 6–20 scale [33, 34] to understand perceptual effects of the SFT and gear.

2.4 Statistical Analysis

All outcome variables were assessed for normality using the Shapiro-wilks test and visual inspection of Q-Q plots. To determine equivalence, a two one-sided paired samples t-test (TOST) [35, 36] was run to determine equivalence between Equivital and DataTherm assessments. Additionally, a Bland-Altman Plot was utilized including equivalence bounds set at mean differences of ± 0.5°C. Equivalence bounds were determined using a combination of previous research studies [37–39]. Specifically, acceptable error ranged from ± 0.40°C in cyclists to ± 0.5 to ± 0.63°C in tactical athletes [37, 39]. Lin’s Concordance Correlation (LCC) was used to determine agreement between the Equivital estimated core temperature and measured DataTherm rectal core temperatures assessment.

Equivital estimated core temperature and DataTherm measurements were averaged over 5-minute epochs to compare differences in core temperature drift between devices. The first epoch (i.e., minutes 1–5) was used as the origin and was subtracted from all subsequent epochs to normalize changes in core body temperature to each participant’s trial day baseline. These 5-minute core temperature epochs were analyzed using a three-way repeated measures ANOVA (device x time x condition) to determine any differences in temperature drift between the two devices across both conditions. Finally, to compare the effects of wearing the firefighter turnout gear against recreational clothing we ran a MANOVA (time x clothing) to assess multivariate differences of physiological data measured by the Equivital (estimated core temperature, skin temperature, heart rate, and ventilatory rate). Five-minute averages were calculated for these physiological variables under each condition (i.e., recreational clothing or the fire fighter turnout gear) and RPE was collected at the end of each 5-minute segment. An ANOVA was also completed to investigate the potential differences in rating of perceived exertion (RPE) induced by turn out gear. Previous research indicating cumulative heat exposure in addition to maximal core temperature [40] prompted an exploratory aim in which we calculated area under the curve (AUC) to assess total heat exposure. The use of AUC as a metric of cumulative heat strain experienced accounts for the temperature reached and the time spent at elevated core temperatures. Five-minute change scores underwent trapezoidal summation to calculate total AUC. Student’s t test was used to compare potential AUC heat stress between recreation clothing or firefighter turnout gear under identical exercise and environmental conditions. All significance was set a priori to p < 0.05. Statistics were run in jamovi 2.0.0.0 [41] and R Studio 4.1.0 [42].

3.1 Descriptive Statistics

Thirteen individuals (Males = 8 Females = 5; Age: 27.1 ± 5.0 yrs; Height: 172.5 ± 8.7 cm; Weight: 80.1 ± 11.7 kg) were included in analysis. Physiological responses (core temperature means and maximum values) to the SFT are included in Table 1.

Table 1. Values reported as mean ± standard deviation during the 40-minute simulated firefighting tasks. Average: The average value across both conditions. Borg 6–20 RPE scale was used of Rating of Perceived Exertion

Table 1

Physiological Strain Average and Maximal Values
Variable	Recreational Clothing (mean; max)	Turnout Gear (mean; max)
Equivital Core Temperature (°C)	37.71 ± 0.30; 38.08 ± 0.36	37.89 ± 0.26; 38.46 ± 0.38
Rectal Core Temperature (°C)	37.62 ± 0.24; 38.02 ± 0.36	37.81 ± 0.26; 38.42 ± 0.24
Heart Rate (bpm)	126.83 ± 15.26; 146.00 ± 16.40	141.09 ± 15.50; 163.54 ± 18.21
Ventilatory Rate (breaths/min)	25.44 ± 3.77; 36.15 ± 6.97	26.86 ± 4.33; 38.69 ± 9.58
Skin Temperature (°C)	36.93 ± 0.83; 38.29 ± 0.62	37.08 ± 0.79; 37.42 ± 8.31
Rating of Perceived Exertion	9.57 ± 1.78; 11.31 ± 2.25	11.23 ± 2.01; 18.00 ± 3.07

3.2 Equivital Core Temperature Validation against DataTherm

One thousand and six paired data points were generated across the thirteen participants for the validation analysis. Our equivalence test indicated a significant bias of 0.1°C towards the Equivital overestimating rectal core body temperature measures. Although the Equivital was found to be significantly different from the rectal thermometer, the TOST also found the two measures to be statistically equivalent (Δ_upper p < 0.001, Δ_lower p < 0.001; Estimate = -0.092, 90%CI = − 0.074 to 0.109). The Bland-Altman plot (Fig. 1) suggests a bias: -0.092, 95% Confidence Interval [-0.113, -0.071], Lower Limits of Agreement: -0.761, 90% CI [-0.785, -0.737], and Upper Limits of Agreement: 0.578, 90% CI [0.554, 0.601]). LCC (Fig. 2) determined good concordance [43] between the Equivital core temperature estimation and DataTherm assessment (LCC = 0.623, 95% CI [0.585, 0.658]).

3.3 Core Temperature Drift between the Equivital and DataTherm

There was significant effect of time (p < 0.001) with core temperature and estimated core temperature increasing with longer exposure to the heat chamber and a significance difference between clothing conditions (p = 0.004). However, there was not as significant difference between devices (p = 0.435). There was an interaction of time and clothing (p < 0.001). No other significant interactions were observed in the mixed effects analysis (ps > 0.081). Data is visually represented in Fig. 3.

3.4 Impact of Turn out Gear on Physiological Strain and Perceived Exertion

The MANCOVA included variable collected on the Equivital device (Estimated core temperature, skin temperature, heart rate, and ventilatory rate). Box’s homogeneity of variance was met (p = 0.052) and Shapiro Wilk’s multivariate normality was violated (p < 0.001), therefore Pillai’s Trace (V) was used for interpretation. Time (V = 1.234, p < 0.001) and clothing (V = 0.202, p < 0.001) were significant, however no interaction effect was observed (V = 0.140, p = 0.911). Univariate ANOVAs were run on significant multivariate statistics with all univariate analyses being significant across time (ps < 0.001) and clothing (ps < 0.001). Univariate ANOVAs were not run on null multivariate effects. Data is visually represented in Fig. 4.

Regarding pairwise posthoc tests for the Equivital estimated core temperature, there were consistent significant differences across time (ps < 0.001) with temperature increasing with heat exposure and there was no difference between clothing (p = 0.107). Regarding the pairwise posthoc tests for heart rate, all time points were significantly different (ps < 0.019) except the following paired timepoints; minutes 11–15 vs minutes 16–20 (p = 0.675), minutes 16–20 vs minutes 21–25 (p = 0.312), minutes 21–25 vs minutes 26–30 (p = 0.410), minutes 26–30 vs minutes 31–35 (p = 0.610), and minutes 31–35 vs minutes 36–40 (p = 0.609). Interestingly, the nonsignificant timepoints are consecutive timepoints, yet when available nonconsecutive timepoints remain significant. We observed a significant effect of clothing on heart rate in our pairwise comparisons (p = 0.022), with higher heart rates being observed in the firefighter turnout gear than in recreational clothing.

Time had a significant effect on ventilatory rate (p < 0.001), however upon further investigation it appeared that exercise modality may have been a confounding factor as participants switched from treadmill walking to deadlifting every 5 minutes, the same amount of time as our epochs (pairwise comparisons of 5-minute epochs can be found in Supplemental Table 1. To eliminate this statistical noise within the analysis, we used 10-minute epochs for interpretation by averaging consecutive epochs (one treadmill walking and one deadlifting) (Supplemental Table 2). Based on the analysis of 10-minute epochs, it ventilatory rate in the last 10 minutes of our exercise protocol was significantly higher than the first three 10-minute epochs (ps < 0.010). There were no other significant effects by time regarding ventilatory rate. Furthermore. we did not observe a significant effect of clothing on ventilatory rate (p = 0.410). Regarding skin temperature, we observed pairwise differences across all time points (ps < 0.013) but no effect from clothing (p = 0.143).

The repeated measures ANOVA investigating perception of exertion indicated a significant effect of time (p < 0.001) and condition (p = 0.010), but no interaction effect of time by condition (p = 0.538) for RPE. Pairwise comparisons indicate that RPE was significantly higher minutes for at 16, 21, 26, 30, 35, and 40 minutes compared to 5 minutes (ps < 0.001). Additionally, RPE was significantly higher at 25, 30, 35, 40 minutes compared than at 10 minutes (ps < 0.040) and 30, 35, 40 were significantly higher than 15 minutes (ps < 0.002). Lastly, RPE at 20 minutes and 25 minutes were significantly higher than at 40 minutes (ps < 0.016). Data is represented visually in Fig. 5 and average and max values for RPE between conditions are included in Table 1.

As an exploratory analysis we conducted trapezoidal summation on rectal core temperature to generate individual area under the curve (AUC) heat responses as a potentially novel method of addressing heat stress and used a t test to compare the differences in heat stress between the clothing condition. AUC was calculated using changes in core temperature over the duration of the exercise protocol. These changes were calculated by subtracting the average of the first 5-minute epoch from all succeeding 5-minute epochs. The t test concluded that there is a significant difference in heat stress as calculated by AUC (p = 0.020, d = 9.47) (Fig. 6).

We are among the first to investigate of the validity of the Equivital core temperature monitoring system in comparison to DataTherm measurements during simulated firefighting in a laboratory setting. In agreeance with our primary hypothesis, our results suggest that the Equivital heart rate derived estimation of core temperature provides sufficiently reliable values when compared to DataTherm rectal core temperatures during simulated firefighting tasks. While the correlation coefficient suggests a moderate-strong relationship between the measures; the two one sided t-test also suggests the measures are statistically equivalent. The Equivital did estimate a significantly higher average core temperature, however this difference was + 0.1°C. and is supported by 0.09°C bias observed from the Bland-Altman Plot (Fig. 1), and this is known not to represent a clinically relevant difference in core temperature [44]. Our finding of + 0.1°C is substantially smaller than the 0.4°C difference determined as acceptable in previous research [45].

Previous research investigating the use of the Equivital algorithm found that the Equivital Black Ghost system underestimated core temperature by ~ 0.75°C with up to 1.7°C variation when compared to injestable core temperature monitoring pills [25]. The divergence between our results and previous work is most likely due to equipment choice and subsequent potential differences in methodology resulting from different devices used (i.e., temperature monitoring pills vs rectal thermometers). In the previous investigation, participants completed a variety of tasks at different durations commonly used during firefighter training to simulate activities commonly encountered during active fireground conditions. However, recent data indicates that a majority (~ 80%) of firefighters’ calls are non-fireground activities (i.e., highway extractions, and medical calls) [26]. Therefore, the present findings provide generalizable results related to the typical day-to-day occupational demands required of firefighters during non-fireground tasks.

In contradiction to our second hypothesis, we observed no difference in the rate of core temperature increase during the SFT between the Equivital Black Ghost estimated core temperature and DataTherm measures regardless of time or condition. Core temperature rose at different rates than when in recreational clothing suggesting greater increases in core temperature and estimated core temperature in the firefighter turnout gear with longer exposure to the heat chamber when compared to core temperatures in recreational clothing under equivalent heat exposures. However, even though the turnout gear results in a difference in core temperature increases, the agreement between devices was unaffected. These finding suggest that the difference between the Equivital estimated core temperature and rectal thermometer measurements do not significantly diverge during prolonged exercise in hot temperatures. The heart rate derived algorithm appears to be robust enough to handle this difference without leading to significant differences in core temperature estimates. It is however worth noting that while not significantly different as exercise continued the average change in estimated core temperature was larger than the change in rectal core temperature until the final ten minutes of exercise when wearing turn out gear. This should be considered for future work investigating whether continued exercise in this environment with turn out gear would further lead to a significant divergence in the estimated core temperatures validity.

When results from our primary and secondary aim are taken together (the agreeability across temperatures, over time, and between clothing conditions) they suggest that the Equivital and black ghost software core temperature algorithm is a consistent and viable estimate for core temperature in research settings and may be an effective tool for core temperature monitoring during non-fireground activities. While it did overestimate core temperature by 0.1°C, we believe this may add to the utility of the Equivital estimation as not only is the device less invasive than a rectal thermometer but may also add to the safety of a trial as research participants will also be removed from heat stressors before imminent, and potentially irreversible, consequences.

In partial agreement to our additional secondary aim, we did see a significant impact of turnout gear on physiological strain. Our multivariate analysis of all Equivital data indicates that these variables differed over time and by clothing condition. Post-hoc univariate analysis of each variable however shows that the difference in clothing was driven by heart rate, as this was the only variable significantly affected by turn out gear. This difference in heart rate was likely due to the added external load created by the weight of the turnout gear (~ 20lbs). As the Black ghost software uses heart rate as a variable of estimating core temperature, the differences in heart rate across condition may explain its ability to overcome core temperature differences and still maintain an accurate assessment of core temperature between clothing conditions; confirmed by the equivalence between Equivital core temperature estimate and DataTherm rectal core temperature measurement.

Additionally, we have also further elucidated the cumulative heat stress created by firefighter turnout gear through our exploratory aim assessing AUC as a novel assessment of cumulative heat stress for rectal core temperature between simulated firefighting trials with and without turnout gear. When comparing AUC’s, we observed a significant difference in total heat stress between clothing. This suggests that turn-out gear itself may induce a significant increase in physiological strain from heat. It is worth noting that core temperature, heart rate, and skin temperature, while not significantly, due appear to increase more rapidly in turnout gear and with future investigations with a longer duration and larger sample size we may see the interaction of gear and time influence these variables. However, previous research has shown increased physiological strain with much shorter and longer durations of activity involving maximal treadmill testing and simulated firefighting task circuits [46–48]. In contradiction to this, other research in wildland firefighters [49] indicated little impact of full PPE (i.e. boots, helmet, gloves, neck shroud, and googles) on heart rate, oxygen consumption, core temperature, skin temperature, and physiological strain index during the first 60–100 minutes of treadmill walking when compared to wearing protective clothing alone [49]. Theses difference in findings could related again to the significant load of turnout gear which can differ from standard wildland firefighting gear and the selection of tasks used to mimic firefighting activities.

Even though there were not significant differences in physiological strain associated with the gear, other than heart rate, our investigation did show perceived exertion was significantly higher and increased more rapidly over time while participants were wearing turn out gear when compared with recreational clothing. These findings suggest there may be a disproportionate rise in perception of exertion in the absence of increased physiological strain due to the turn out gear. This could be due to thermal discomfort from the insulative properties of turn out gear. However, this is speculative and based on previous research that highlighted the thermal discomfort of firefighter gear [50] as we did not assess thermal discomfort in this investigation. Other previous research has elucidated negative effects of turnout gear on mobility and performance [11, 51]. The results of these previous investigation in addition to our finding may suggest that limitations in mobility, perceived exertion, and thermal discomfort may impact performance in turn out gear more than actual differences in physiological responses.

The present investigation has demonstrated that the Equivital and Black Ghost software is an accurate, noninvasive, and safe method of estimating core body temperature in healthy young adults. Future investigations should ensure adequate age diversity within their samples to improve the generalizability of these findings considering the diverse age, fitness, and health characteristics of current United States firefighters [52]. We believe a strength of the present investigation is the representation of females in firefighter research and encourage future investigations to continue this effort to maintain representation and rigor proposed by the National Health Institute [53]. In addition, the use of core temperature AUC as a measure of cumulative heat stress may be a valuable workload monitoring tool specifically in firefighters and other outdoor occupational workers that experience multiple bouts or extended heat exposure during their workday. Previous work in underground miners suggest this concept of the dynamic patterns of heat strain over time has a larger impact on heat related injury risk than maximum temperature reached [1, 40]. These results in addition to the data presented in the current study warrant future investigation into the implementation of core temperature AUC monitoring.

A potential limitation of our study was that researchers did not verify appropriate insertion of the probe prior to beginning the exercise bout and could not control and potential movement of the probe once the exercise bout began. However, participants were given detailed insertion instructions and offered visual assistance of a permanent mark on the probe to ensure full (15 cm) insertion and were provided adhesive tape to secure the probe in place prior to experimental testing. Additionally, while understanding the limitations of the rectal thermometer, we believe the use of the rectal core temperature was appropriate given that it remains the gold standard for core temperature assessment and that ingestible temperature pills present their own unique problems (ingestion timing, recent food consumption, and hydration). An additional limitation is that while the movements chosen for the SFT were in accordance with departmental leadership of the local fire department, these movement patterns may not precisely reflect activity achieved during occupational tasks in real emergency scenarios. However, these movements were chosen in efforts to mimic the most common movement patterns given the confines of our environmental chamber. Additionally, a strength of our study aimed to investigate the validity of the Equivital in the non-fireground activities. Even though these environments are most common for firefighters, future directions from this project include validating the Equivital in more extreme environments (i.e., structural fires or live-burn training), to determine whether the device would provide adequate, real-time assessments of thermal stress in life-or-death situations to which firefighters may frequently be exposed.

The use of an environmental chamber effectively provided a consistent and reliable control of heat and humidity that is not possible in field-testing environments. Control of these environmental factors reduces confounding variables related to the environment, however, solar radiation and substantial airflow are absent; both of which play a role in human thermoregulatory responses and may impact core temperature and heart rate based estimates of core temperature uniquely [54]. Furthermore, participants in our study only wore turn-out gear while lacking boots and a helmet. A 2014 study established component contribution of firefighting gear during 30-minutes of walking at 5.5 km/h [12]. These findings highlighted that removing standard firefighting boots significantly reduced the physiological strain experienced due to boots being mechanically insufficient and restricting heat dissipation from the feet [12]. However, the previously mentioned study in wildland firefighters indicated little impact of full PPE (i.e. boots, helmet, gloves, neck shroud, and googles) [49]. This may suggest that the type of gear worn by wildland firefighters compared to structural firefighters may have a differential impact on physiological strain and heat related injury risk. Future work should consider both the component contribution of gear and outdoor thermoregulatory factors that may impact the validity of this monitoring tool.

This study indicates that Equivital EQ02 + LifeMonitor and Black Ghost software provides a reliable, less invasive, alternative method of continuous core temperature monitoring when performing firefighter occupational tasks with and without turnout gear. Our results support the Equivital as an effective core temperature monitoring system in the laboratory research setting and potentially for non-fireground activities. This study demonstrated that as exercise in heat continues and core temperature rises, the agreeability of the Equivital estimated core temperature and DataTherm II rectal core temperature measures remain consistent. This study also provides evidence that turnout gear significantly impacts perceived exertion and heart rate, but not other measures of physiological strain (ventilation, core temperature, and skin temperature) experienced during simulated firefighting activities, with duration of exertion and heat exposure being more indicative of increases in physiological strain.

Acknowledgments: We would like to thank our research volunteers for assisting with data collection, and the participants for their time and efforts.

Funding: B.L. was supported by NIH grant UL1TR003096 TL-1 Fellowship and XXX University Presidential Graduate Student Research Fellowship.

Consent to participate: Informed consent was obtained from all individual participants included in the study.

Ethical Approval: The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of XXX (protocol code #22-149 MR 2205, 05/05/2022).

Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Data Availability: The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

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Validity of Heart Rate Derived Core Temperature Estimation During Simulated Firefighting Tasks

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Version 1

Abstract

Figures

1 Introduction

2 Methods

2.1 Participants

2.2 Research design

2.3 Experimental Trials

2.3.1 Simulated Firefighting Tasks (SFT)

2.3.2 Physiological Strain Measures

2.4 Statistical Analysis

3 Results

3.1 Descriptive Statistics

3.2 Equivital Core Temperature Validation against DataTherm

3.3 Core Temperature Drift between the Equivital and DataTherm

3.4 Impact of Turn out Gear on Physiological Strain and Perceived Exertion

4 Discussion

5 Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1