Miyo Yokota

Thermoregulatory model to predict physiological status from ambient environment and heart rate

A real-time thermoregulatory model was developed for predicting real-time physiological responses of workers engaged in various tasks for prolonged time. The unique feature of the present model is primarily on metabolic activity inputs derived from minimum non-invasive measures (i.e., heart rate and ambient temperature). In addition, it utilizes individual anthropological characteristics (height, weight, and clothing) as an input to estimate core temperatures (T(c)). The model was validated using data from five laboratory studies (n=63) with varied environments, clothing, and heat acclimation status. Overall, T(c) predictions using this simplified model, corresponded well with measured values (root mean square deviation: 0.05-0.31 degrees C).

Total energy expenditure estimated using foot-ground contact pedometry.

Routine walking and running, by increasing daily total energy expenditure (TEE), can play a significant role in reducing the likelihood of obesity. The objective of this field study was to compare TEE estimated using foot-ground contact time (Tc)-pedometry (TEE(PEDO)) with that measured by the criterion doubly labeled water (DLW) method. Eight male U.S. Marine test volunteers [27 +/- 4 years of age (mean +/- SD); weight = 83.2 +/- 10.7 kg; height = 182.2 +/- 4.5 cm; body fat = 17.0 +/- 2.9%] engaged in a field training exercise were studied over 2 days. TEE(PEDO) was defined as (calculated resting energy expenditure + estimated thermic effect of food + metabolic cost of physical activity), where physical activity was estimated by Tc-pedometry. Tc-pedometry was used to differentiate inactivity, activity other than exercise (i.e., non-exercise activity thermogenesis, or NEAT), and the metabolic cost of locomotion (M(LOCO)), where M(LOCO) was derived from total weight (body weight + load weight) and accelerometric measurements of Tc. TEE(PEDO) data were compared with TEEs measured by the DLW (2H2(18)O) method (TEE(DLW)): TEE(DLW) = 15.27 +/- 1.65 MJ/day and TEE(PEDO) = 15.29 +/- 0.83 MJ/day. Mean bias (i.e., TEE(PEDO) - TEE(DLW)) was 0.02 MJ, and mean error (SD of individual differences between TEE(PEDO) and TEE(DLW)) was 1.83 MJ. The Tc-pedometry method provided a valid estimate of the average TEE of a small group of physically active subjects where walking was the dominant activity.

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

First responders often wear personal protective equipment (PPE) for protection from on-the-job hazards. While PPE ensembles offer individuals protection, they limit ones 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 algorithms bias and variance to observed data were similar to that found from comparisons of oesophageal and rectal measurements.

Thermal-work strain in law enforcement personnel during chemical, biological, radiological, and nuclear (CBRN) training

Abstract Background: Thermal safety standards for the use of chemical, biological, radiological, and nuclear (CBRN) ensembles have been established for various US occupations, but not for law enforcement personnel. Objectives: We examined thermal strain levels of 30 male US law enforcement personnel who participated in CBRN field training in Arizona, Florida, and Massachusetts. Methods: Physiological responses were examined using unobtrusive heart rate (HR) monitors and a simple thermoregulatory model to predict core temperature (Tc) using HR and environment. Results: Thermal strain levels varied by environments, activity levels, and type of CBRN ensemble. Arizona and Florida volunteers working in hot-dry and hot-humid environment indicated high heat strain (predicted max Tc>38·5°C). The cool environment of Massachusetts reduced thermal strain although thermal strains were occasionally moderate. Conclusions: The non-invasive method of using physiological monitoring and thermoregulatory modeling could improve law enforcement mission to reduce the risk of heat illness or injury.

Real-time Non-invasive Heat Strain Prediction Model

Core temperature (Tc) is an excellent indicator of heat strain status. A computer model, Initial Capability Decision Aid (ICDA), was developed from existing models and algorithms to predict Tc and other physiological parameters in real-time from noninvasively measured inputs of heart rate (HR) and environment parameters together with the person’s clothing and anthropometrics. The model was validated with laboratory studies. Tc prediction errors were small (0.11~0.31oC). Predictions of sweat rate and physiological strain index also agreed well (p>0.05) with measured values.