A non-invasive device to continuously determine heat strain in humans

Noninvasive Temperature Measurements in Tissue-Simulating Phantoms Using a Solid-State Near-Infrared Sensor

The monitoring of body temperature is a recent addition to the plethora of parameters provided by wellness and fitness wearable devices. Current wearable temperature measurements are made at the skin surface, a measurement that is impacted by the ambient environment of the individual. The use of near-infrared spectroscopy provides the potential for a measurement below the epidermal layer of skin, thereby having the potential advantage of being more reflective of physiological conditions. The feasibility of noninvasive temperature measurements is demonstrated by using an in vitro model designed to mimic the near-infrared spectra of skin. A miniaturizable solid-state laser-diode-based near-infrared spectrometer was used to collect diffuse reflectance spectra for a set of seven tissue phantoms composed of different amounts of water, gelatin, and Intralipid. Temperatures were varied between 20-24 °C while collecting these spectra. Two types of partial least squares (PLS) calibration models were developed to evaluate the analytical utility of this approach. In both cases, the collected spectra were used without pre-processing and the number of latent variables was the only optimized parameter. The first approach involved splitting the whole dataset into separate calibration and prediction subsets for which a single optimized PLS model was developed. For this first case, the coefficient of determination (R2) is 0.95 and the standard error of prediction (SEP) is 0.22 °C for temperature predictions. The second strategy used a leave-one-phantom-out methodology that resulted in seven PLS models, each predicting the temperatures for all spectra in the held-out phantom. For this set of phantom-specific predicted temperatures, R2 and SEP values range from 0.67-0.99 and 0.19-0.65 °C, respectively. The stability and reproducibility of the sample-to-spectrometer interface are identified as major sources of spectral variance within and between phantoms. Overall, results from this in vitro study justify the development of future in vivo measurement technologies for applications as wearables for continuous, real-time monitoring of body temperature for both healthy and ill individuals.

Noninvasive and Continuous Monitoring of the Core Body Temperature through the Quantitative Measurement of Blood Perfusion Rate

Core body temperature (CBT) is one of the four vital signs that must be monitored continuously. The continuous recording of CBT is possible through invasive methods by inserting a temperature probe into specific body sites. We report a novel method to monitor CBT through the quantitative measurement of skin blood perfusion rate (ωb,skin). By monitoring the skin temperature, heat flux, and ωb,skin, the arterial blood temperature, equivalent to CBT, can be extracted. ωb,skin is quantitatively evaluated thermally via sinusoidal heating with regulated thermal penetration depth so that the blood perfusion rate is acquired only in the skin. Its quantification is significant because it indicates various physiological events including hyper- or hypothermia, tissue death, and delineation of tumors. A subject showed promising results with steady values of ωb,skin and CBT of 5.2 ± 1.05 × 10-4 s-1 and 36.51 ± 0.23 °C, respectively. For periods where the subject's actual CBT (axillary temperature) did not fall within the estimated range, the average deviation from the actual CBT was only 0.07 °C. This study aims to develop a competent methodology capable of continuously monitoring the CBT and blood perfusion rate at a distant location from the core body region for the diagnosis of a patient's health condition with wearable devices.

Heat flux systems for body core temperature assessment during exercise

Heat flux systems are increasingly used to assess core body temperature. However, validation of multiple systems is scarce. Therefore, an experiment was performed in which three commercially available heat flux systems (3 M, Medisim and Core) were compared to rectal temperature (T_re). Five females and four males performed exercise in a climate chamber set at 18 °C/50% relative humidity until exhaustion. Exercise duration was 36.3 ± 5.6 min (mean ± standard deviation). T_re in rest was 37.2 ± 0.3 °C. Medisim's-values were lower than T_re (36.9 ± 0.4 °C, p < 0.05); 3 M (37.2 ± 0.1 °C) and Core's (37.4 ± 0.3 °C) did not differ from T_re. Maximal temperatures after exercise were 38.4 ± 0.2 °C (T_re), 38.0 ± 0.4 °C (3 M), 38.8 ± 0.3 °C (Medisim) and 38.6 ± 0.3 °C (Core); Medisim was significantly higher than T_re (p < 0.05). The temperature profiles of the heat flux systems during exercise differed to varying degree from the rectal profiles; the Medisim system showed a faster increase during exercise than T_re (0.48 ± 0.25 °C in 20 min, p < 0.05), the Core system tended to show a systematic overestimation during the entire exercise period and the 3 M system showed large errors at the end of exercise, likely due to sweat entering the sensor. Therefore, the interpretation of heat flux sensor values as core body temperature estimates should be done with care; more research is required to elucidate the physiological significance of the generated temperature values.

Biomarkers for warfighter safety and performance in hot and cold environments

Exposure to extreme environmental heat or cold during military activities can impose severe thermal strain, leading to impairments in task performance and increasing the risk of exertional heat (including heat stroke) and cold injuries that can be life-threatening. Substantial individual variability in physiological tolerance to thermal stress necessitates an individualized approach to mitigate the deleterious effects of thermal stress, such as physiological monitoring of individual thermal strain. During heat exposure, measurements of deep-body (T_c) and skin temperatures and heart rate can provide some indication of thermal strain. Combining these physiological variables with biomechanical markers of gait (in)stability may provide further insight on central nervous system dysfunction - the key criterion of exertional heat stroke (EHS). Thermal strain in cold environments can be monitored with skin temperature (peripheral and proximal), shivering thermogenesis and T_c. Non-invasive methods for real-time estimation of T_c have been developed and some appear to be promising but require further validation. Decision-support tools provide useful information for planning activities and biomarkers can be used to improve their predictions, thus maximizing safety and performance during hot- and cold-weather operations. With better understanding on the etiology and pathophysiology of EHS, the microbiome and markers of the inflammatory responses have been identified as novel biomarkers of heat intolerance. This review aims to (i) discuss selected physiological and biomechanical markers of heat or cold strain, (ii) how biomarkers may be used to ensure operational readiness in hot and cold environments, and (iii) present novel molecular biomarkers (e.g., microbiome, inflammatory cytokines) for preventing EHS.

Wearable Sensor Technology to Predict Core Body Temperature: A Systematic Review

Heat-related illnesses, which range from heat exhaustion to heatstroke, affect thousands of individuals worldwide every year and are characterized by extreme hyperthermia with the core body temperature (CBT) usually > 40 °C, decline in physical and athletic performance, CNS dysfunction, and, eventually, multiorgan failure. The measurement of CBT has been shown to predict heat-related illness and its severity, but the current measurement methods are not practical for use in high acuity and high motion settings due to their invasive and obstructive nature or excessive costs. Noninvasive predictions of CBT using wearable technology and predictive algorithms offer the potential for continuous CBT monitoring and early intervention to prevent HRI in athletic, military, and intense work environments. Thus far, there has been a lack of peer-reviewed literature assessing the efficacy of wearable devices and predictive analytics to predict CBT to mitigate heat-related illness. This systematic review identified 20 studies representing a total of 25 distinct algorithms to predict the core body temperature using wearable technology. While a high accuracy in prediction was noted, with 17 out of 18 algorithms meeting the clinical validity standards. few algorithms incorporated individual and environmental data into their core body temperature prediction algorithms, despite the known impact of individual health and situational and environmental factors on CBT. Robust machine learning methods offer the ability to develop more accurate, reliable, and personalized CBT prediction algorithms using wearable devices by including additional data on user characteristics, workout intensity, and the surrounding environment. The integration and interoperability of CBT prediction algorithms with existing heat-related illness prevention and treatment tools, including heat indices such as the WBGT, athlete management systems, and electronic medical records, will further prevent HRI and increase the availability and speed of data access during critical heat events, improving the clinical decision-making process for athletic trainers and physicians, sports scientists, employers, and military officers.

Acute Thermoregulatory and Cardiovascular Response to Submaximal Exercise in People With Multiple Sclerosis

Background

Heat sensitivity occurs in a high percentage of people with multiple sclerosis (PwMS), in response to environmental or exercise-induced increase in body temperature. However, the kinetic and magnitude of adaptation of the internal load and of the core body temperature (CBT) to a submaximal continuous exercise has been poorly addressed in PwMS; this may be relevant for the brief exercise bouts usually occurring in normal daily life. The aim of this work was to evaluate whether multiple sclerosis influences the acute adaptation of the internal load, the CBT and the perceptual load in response to a constant submaximal work step.

Methods

CBT has been continuously monitored (0.5 Hz) by a validated wearable heat-flux sensor and electrocardiography was recorded (250 Hz) by a wearable device during a standard 6-minute walk test (6MWT) in 14 PwMS (EDSS, 4.7 ± 1.2; disease duration: 13.0 ± 10.2 years; m ± SD) and 14 age, sex and BMI-matched healthy subjects (HS). The rate of perceived exertion (RPE) of the lower limbs was assessed during the 6MWT by the Borg scale (6-20).

Results

As expected, PwMS walked a significantly shorter distance (361 ± 98 m) than the HS group (613 ± 62 m, p<0.001 vs PwMS). However, the kinetics of adaptation of CBT and the magnitude of CBT change from baseline did not differ between groups. Similarly, heart rate (HR) kinetics and HR change from baseline were comparable between groups during the 6MWT. Finally, lower limbs RPE gradually increased during the exercise test, but without significant differences between groups.

Conclusion

The internal load, the metabolic heat production, and the perceptive load due to a standard submaximal walking exercise seems to be preserved in PwMS, suggesting a comparable acute heat production and dissipation during exercise. Therefore, it is unlikely that the different distance achieved during the 6MWT may be caused by altered thermoregulatory responses to exercise. Rather, this appears to be a consequence of the known increased energy cost of locomotion in PwMS.

Optimization of a Stacked-design Core-body-temperature Sensor for Long-period Human Trials

We fabricated a wearable sensor that can be attached to the skin surface and continuously measure core body temperature (CBT) wirelessly over a long period. CBT is calculated from skin-surface temperature and heat flux passing through the sensor. Since heat flux is lost to the surroundings of the probe, the slightest change in convection in daily life will degrade the measurement accuracy of the sensor. Accordingly, we previously proposed a heat-flux-path control structure to reduce the absolute amount of heat-flux loss. To make wearable sensors for long-term human trials, we proposed an integrated design in which a sensor probe, a circuit board, and a battery are stacked. We optimized the proposed design by computer simulation and evaluated the fabricated sensor by a phantom experiment in which the convectional state was changed. The evaluation results demonstrate that the sensor has limits of agreement (LOA) of [-0.13; 0.03]°C under 1-m/s-wind convection. Moreover, a preliminary human trial conducted under daily-life conditions (including convectional changes) demonstrated that the sensor has LOA of [-0.18; 0.22]°C. These results demonstrate that the fabricated sensor is suitable for CBT measurement.

Low Ambient Temperature Exposition Impairs the Accuracy of a Non-invasive Heat-Flux Thermometer

Background

Indirect core body temperature (CBT) monitoring from skin sensors is gaining attention for in-field applications thanks to non-invasivity, portability, and easy probe positioning. Among skin sensors, heat-flux devices, such as the so-called Double Sensor (DS), have demonstrated reliability under various experimental and clinical conditions. Still, their accuracy at low ambient temperatures is unknown. In this randomized cross-over trial, we tested the effects of cold temperature exposition on DS performance in tracking CBT.

Methods

Twenty-one participants were exposed to a warm (23.2 ± 0.4°C) and cold (−18.7 ± 1.0°C) room condition for 10 min, following a randomized cross-over design. The accuracy of the DS to estimate CBT in both settings was assessed by quantitative comparison with esophageal (reference) and tympanic (comparator) thermometers, using Bland–Altman and correlation analyses (Pearson’s correlation coefficient, r, and Lin’s concordance correlation coefficient, CCC).

Results

In the warm room setting, the DS showed a moderate agreement with the esophageal sensor [bias = 0.09 (−1.51; 1.69) °C, r = 0.40 (p = 0.069), CCC = 0.22 (−0.006; 0.43)] and tympanic sensor [bias = 2.74 (1.13; 4.35) °C, r = 0.54 (p < 0.05), CCC = 0.09 (0.008; 0.16)]. DS accuracy significantly deteriorated in the cold room setting, where DS temperature overestimated esophageal temperature [bias = 2.16 (−0.89; 5.22) °C, r = 0.02 (0.94), CCC = 0.002 (−0.05; 0.06)]. Previous exposition to the cold influenced temperature values measured by the DS in the warm room setting, where significant differences (p < 0.00001) in DS temperature were observed between randomization groups.

Conclusion

DS accuracy is influenced by environmental conditions and previous exposure to cold settings. These results suggest the present inadequacy of the DS device for in-field applications in low-temperature environments and advocate further technological advancements and proper sensor insulation to improve performance in these conditions.

Noninvasive Versus Invasive Brain Temperature Measurement During Targeted Temperature Management: A Preclinical Study in a Swine Cardiac Arrest Model

We aimed to evaluate correlation and agreement between noninvasive brain temperature (T_BN) and invasive brain temperature (T_BI) measurement during targeted temperature management (TTM) in a swine cardiac arrest model. Defibrillation attempts were provided after 5 minutes of ventricular fibrillation and 12 minutes of cardiopulmonary resuscitation in five pigs. After return of spontaneous circulation, TTM was provided with induction and maintenance phases with a target temperature of 33°C for 6 hours and a rewarming phase with a rewarming rate of 1°C/h for 4 hours. T_BN and T_BI were measured using a double sensor method and an intracranial catheter, respectively. Pulmonary artery temperature (T_P), esophageal temperature (T_E), and rectal temperature (T_R) were measured. Primary outcomes were correlation and agreement between T_BN and T_BI and secondary outcomes were correlation and agreement among T_BN and other temperatures. The Pearson correlation coefficient (PCC) between T_BN and T_BI was 0.95 (p < 0.001) during the whole TTM phases. PCCs between T_BN and T_BI during the induction, maintenance, and rewarming phases were 0.91 (p < 0.001), 0.88 (p < 0.001), and 0.94 (p < 0.001) and 95% limits of agreement (LoAs) between T_BN and T_BI were (-0.27°C to 0.78°C), (-0.18°C to 0.54°C), and (-0.93°C to 0.88°C), respectively. Correlation between T_BN and T_BI during the maintenance phase was higher than correlation between T_BN and T_E (PCC = 0.74, p < 0.001) or T_P (PCC = 0.81, p < 0.001). The 95% LoAs were narrowest between T_BN and T_P in the induction phase (-0.58 to 0.11), between T_BN and T_BI in the maintenance phase (-0.54 to 0.18), and between T_BN and T_R in the rewarming phase (-0.96 to 0.84). Noninvasive brain temperature showed good correlation with invasive brain temperature during TTM in a swine cardiac arrest model. Correlation was highest during the rewarming phase and lowest during the maintenance phase. Agreement between the two measurements was not clinically acceptable.

Predicting Deep Body Temperature (Tb) from Forehead Skin Temperature: Tb or Not Tb?

There is a need to rapidly screen individuals for heat strain and fever using skin temperature (T_sk) as an index of deep body temperature (T_b). This study’s aim was to assess whether T_sk could serve as an accurate and valid index of T_b during a simulated heatwave. Seven participants maintained a continuous schedule over 9-days, in 3-day parts; pre-/post-HW (25.4 °C), simulated-HW (35.4 °C). Contact thermistors measured T_sk (T_forehead, T_finger); radio pills measured gastrointestinal temperature (T_gi). Proximal-distal temperature gradients (ΔT_{forehead–finger}) were also measured. Measurements were grouped into ambient conditions: 22, 25, and 35 °C. T_gi and T_forehead only displayed a significant relationship in 22 °C (r: 0.591; p < 0.001) and 25 °C (r: 0.408; p < 0.001) conditions. A linear regression of all conditions identified T_forehead and ΔT_{forehead–finger} as significant predictors of T_gi (r²: 0.588; F: 125.771; p < 0.001), producing a root mean square error of 0.26 °C. Additional residual analysis identified T_forehead to be responsible for a plateau in T_gi prediction above 37 °C. Contact T_forehead was shown to be a statistically suitable indicator of T_gi in non-HW conditions; however, an error of ~1 °C makes this physiologically redundant. The measurement of multiple sites may improve T_b prediction, though it is still physiologically unsuitable, especially at higher ambient temperatures.

Comparison of zero heat flux and double sensor thermometers during spinal anaesthesia: a prospective observational study

Because of the difficulties involved in the invasive monitoring of conscious patients, core temperature monitoring is frequently neglected during neuraxial anaesthesia. Zero heat flux (ZHF) and double sensor (DS) are non-invasive methods that measure core temperature from the forehead skin. Here, we compare these methods in patients under spinal anaesthesia. Sixty patients scheduled for elective unilateral knee arthroplasty were recruited and divided into two groups. Of these, thirty patients were fitted with bilateral ZHF sensors (ZHF group), and thirty patients were fitted with both a ZHF sensor and a DS sensor (DS group). Temperatures were saved at 5-min intervals from the beginning of prewarming up to one hour postoperatively. Bland–Altman analysis for repeated measurements was performed and a proportion of differences within 0.5 °C was calculated as well as Lin`s concordance correlation coefficient (LCCC). A total of 1261 and 1129 measurement pairs were obtained. The mean difference between ZHF sensors was 0.05 °C with 95% limits of agreement − 0.36 to 0.47 °C, 99% of the readings were within 0.5 °C and LCCC was 0.88. The mean difference between ZHF and DS sensors was 0.33 °C with 95% limits of agreement − 0.55 to 1.21 °C, 66% of readings were within 0.5 °C and LCCC was 0.59. Bilaterally measured ZHF temperatures were almost identical. DS temperatures were mostly lower than ZHF temperatures. The mean difference between ZHF and DS temperatures increased when the core temperature decreased.

Trial registration: The study was registered in ClinicalTrials.gov on 13th May 2019, Code NCT03408197.

Smart Face Mask with an Integrated Heat Flux Sensor for Fast and Remote People's Healthcare Monitoring

The COVID-19 pandemic has highlighted a large amount of challenges to address. To combat the spread of the virus, several safety measures, such as wearing face masks, have been taken. Temperature controls at the entrance of public places to prevent the entry of virus carriers have been shown to be inefficient and inaccurate. This paper presents a smart mask that allows to monitor body temperature and breathing rate. Body temperature is measured by a non-invasive dual-heat-flux system, consisting of four sensors separated from each other with an insulating material. Breathing rate is obtained from the temperature changes within the mask, measured with a thermistor located near the nose. The system communicates by means of long-range (LoRa) backscattering, leading to a reduction in average power consumption. It is designed to establish the relative location of the smart mask from the signal received at two LoRa receivers installed inside and outside an access door. Low-cost LoRa transceivers with WiFi capabilities are used in the prototype to collect information and upload it to a server. Accuracy in body temperature measurements is consistent with measurements made with a thermistor located in the armpit. The system allows checking the correct placement of the mask based on the recorded temperatures and the breathing rate measurements. Besides, episodes of cough can be detected by sudden changes in thermistor temperature.

Wearable Personal Core Body Temperature Measurement Considering Individual Differences and Dynamic Tissue Blood Perfusion

Accurate and continuous measurement of the human core body temperature by a wearable device is of great significance for human health care and disease monitoring. The current wearable thermometers ignore the physiological differences between individuals and the role of blood perfusion in thermoregulation, resulting in insufficient accuracy and limitations in terms of the measurement sites. This study proposed a novel personal model for measuring core body temperature by taking dynamic tissue blood perfusion and individual differences into consideration. The technique facilitates possible accurate core body temperature measurements from the skin surface of the wrist and forehead. First, the personal core body temperature model was established based on the thermal equilibrium between the human body and the measurement device, in which the tissue blood perfusion changes dynamically with tissue temperature. Then, the parameters of the personal model that imply individual physiological differences were obtained based on personal data collected daily. The results show that with the developed personal model, the accuracy of the measured body temperature from the wrist is close to that of the forehead model. The wrist model and the forehead model have a mean absolute error of 0.297 (SD=0.078) C and 0.224 (SD=0.071) C, respectively, which meets the accuracy and robustness requirements of practical applications. The personal models significantly improve the accuracy compared with that of the group model, especially for the wrist model.

Be cool to be far: Exploiting hibernation for space exploration

In mammals, torpor/hibernation is a state that is characterized by an active reduction in metabolic rate followed by a progressive decrease in body temperature. Torpor was successfully mimicked in non-hibernators by inhibiting the activity of neurons within the brainstem region of the Raphe Pallidus, or by activating the adenosine A1 receptors in the brain. This state, called synthetic torpor, may be exploited for many medical applications, and for space exploration, providing many benefits for biological adaptation to the space environment, among which an enhanced protection from cosmic rays. As regards the use of synthetic torpor in space, to fully evaluate the degree of physiological advantage provided by this state, it is strongly advisable to move from Earth-based experiments to 'in the field' tests, possibly on board the International Space Station.

Construct validity and invariance assessment of the social impacts of occupational heat stress scale (SIOHSS) among Ghanaian mining workers

Heat exposure studies over the last decade have shown little attention in assessing and reporting the psychometric properties of the various scales used to measure impacts of occupational heat stress on workers. A descriptive cross-sectional survey including 320 small- and large-scale mining workers was employed to assess the construct validity of the social impacts of occupational heat stress scale (SIOHSS) in the Western Region of Ghana in 2017. A confirmatory factor analysis (CFA) and invariance analysis were carried out using AMOS version 25 and statistical product and service solutions (SPSS) version 26 to examine the model fit and establish consistency correspondingly across multiple groups (gender, age, working hours, type of mining and workplace setting). Empirically, our results depicted that effects on health and safety, behavioural, productivity and social well-being were each found to be reliable, with Cronbach's α of 0.722, 0.807, 0.852 and 0.900 respectively. Though there were issues of insufficient discriminant validity as some average variance extract (AVE) were smaller than the corresponding maximum shared variance (MSV), the CFA showed good model fit indices (CFI = 0.856, GFI = 0.890, TLI = 0.863, SRMR = 0.08, RMSEA = 0.08). Also, the model was variant for all constrained aspects of the structural model indicating a requirement for an adaptation of the instrument across groups. The good to moderate internal consistency and construct validity of the SIOHSS is adequate evidence for the confidence required for its reliability and accuracy in measuring the social impacts of occupational heat stress on workers.

Long-Term Bed Rest Delays the Circadian Phase of Core Body Temperature

Spaceflight can be associated with sleep loss and circadian misalignment as a result of non-24 h light-dark cycles, operational shifts in work/rest cycles, high workload under pressure, and psychological factors. Head-down tilt bed rest (HDBR) is an established model to mimic some of the physiological and psychological adaptions observed in spaceflight. Data on the effects of HDBR on circadian rhythms are scarce. To address this gap, we analyzed the change in the circadian rhythm of core body temperature (CBT) in two 60-day HDBR studies sponsored by the European Space Agency [n = 13 men, age: 31.1 ± 8.2 years (M ± SD)]. CBT was recorded for 36 h using a non-invasive and validated dual-sensor heatflux technology during the 3rd and the 8th week of HDBR. Bed rest induced a significant phase delay from the 3rd to the 8th week of HDBR (16.23 vs. 16.68 h, p = 0.005, g = 0.85) irrespective of the study site (p = 0.416, g = −0.46), corresponding to an average phase delay of about 0.9 min per day of HDBR. In conclusion, long-term bed rest weakens the entrainment of the circadian system to the 24-h day. We attribute this effect to the immobilization and reduced physical activity levels associated with HDBR. Given the critical role of diurnal rhythms for various physiological functions and behavior, our findings highlight the importance of monitoring circadian rhythms in circumstances in which gravity or physical activity levels are altered.

Measuring Core Body Temperature Using a Non-invasive, Disposable Double-Sensor During Targeted Temperature Management in Post-cardiac Arrest Patients

Background: Precisely measuring the core body temperature during targeted temperature management after return of spontaneous circulation is mandatory, as deviations from the recommended temperature might result in side effects such as electrolyte imbalances or infections. However, previous methods are invasive and lack easy handling. A disposable, non-invasive temperature sensor using the heat flux approach (Double Sensor), was tested against the standard method: an esophagus thermometer.

Methods: The sensor was placed on the forehead of adult patients (n = 25, M/F, median age 61 years) with return of spontaneous circulation after cardiac arrest undergoing targeted temperature management. The recorded temperatures were compared to the established measurement method of an esophageal thermometer. A paired t-test was performed to examine differences between methods. A Bland-Altman-Plot and the intraclass correlation coefficient were used to assess agreement and reliability. To rule out possible influence on measurements, the patients' medication was recorded as well.

Results: Over the span of 1 year and 3 months, data from 25 patients were recorded. The t-test showed no significant difference between the two measuring methods (t = 1.47, p = 0.14, n = 1,319). Bland-Altman results showed a mean bias of 0.02°C (95% confidence interval 0.00–0.04) and 95% limits of agreement of −1.023°C and 1.066°C. The intraclass correlation coefficient was 0.94. No skin irritation or allergic reaction was observed where the sensor was placed. In six patients the bias differed noticeably from the rest of the participants, but no sex-based or ethnicity-based differences could be identified. Influences on the measurements of the Double Sensor by drugs administered could also be ruled out.

Conclusions: This study could demonstrate that measuring the core body temperature with the non-invasive, disposable sensor shows excellent reliability during targeted temperature management after survived cardiac arrest. Nonetheless, clinical research concerning the implementation of the sensor in other fields of application should be supported, as well as verifying our results by a larger patient cohort to possibly improve the limits of agreement.

Improved Smart Pillow for Remote Health Care System

The outbreak of novel coronavirus (COVID-19) resulted in the clinical decision that reduced direct contact is optimal, especially for senior citizens residing in nursing homes. A smart pillow adapted for the Remote Healthcare System is presented in this paper, whose core is a Bluetooth (BT) host equipped with temperature and pressure sensors. The measurement of Core Body Temperature (CBT) from the perspective of heat transfer is first analyzed, with two proven effective methods introduced—classical Zero-Heat-Flux (ZHF) and Dual-Heat-Flux (DHF)—then finally the similarities between the Smart Pillow and ZHF are demonstrated. A pressure pad is inserted inside the pillow to detect occupancy and the specific position of the head on the pillow that meets clinical diagnostic needs. Furthermore, a real-time proactive monitoring mode is enabled for urgent warnings, which forces the pillow to keep detecting and reporting data in a defined time duration but results in rapid battery drain of the pillow. In this way, the system can detect the CBT and in-bed situation of the inhabitant without being physically present to determine critical measurements. Utility of this system can be extended to elderly people living alone in regional or remote areas, such that medical help can be dispatched as soon as possible in case of medical emergency.

Assessing rectal temperature with a novel non-invasive sensor

Athletes, soldiers, and workers who perform intense physical activities under extreme hot conditions might encounter increased physiological thermal strain. Consequently, the increase in body core temperature (T_c) might result in heat exhaustion and heatstroke. Thus, continuously following changes in T_c is of utmost importance. Recently, the Tcore sensor (Dräger, Germany), which employs a unique dual-sensor heat flux technology, became commercially available to measure T_c, in a hospital-controlled environment. This study aimed to evaluate the possibility of using the Tcore sensor to accurately monitor rectal temperature (T_re), reflecting T_c, under exercise-heat stress. Thirteen healthy young males completed the study protocol, consisting of 90 min of moderate exercise (walking on a treadmill - 5 km/h, 4% elevation) under controlled hot/dry and hot/wet climatic conditions (30 °C/60% rh, 34 °C/40% rh, and 40 °C/40% rh). Tcore sensors were placed on the forehead and the left wrist. Temperatures from both Tcore sensors were recorded continuously together with T_re using a rectal thermistor. The original algorithm used by the company to estimate T_re from the Tcore sensor was found to be inadequate under the study's conditions and new models for the forehead and the wrist measurements were developed. Nearly 150,000 measurement sets (after filtering) were used to build independent MATLAB software algorithms and test their reliability according to the cross-validation algorithm. Bland-Altman analysis was used to compare between the results obtained by the new models to T_re. The database consisted of a large T_re range (36.5-38.9 °C). The mean errors of the models were close to zero, and the mean absolute errors were 0.20 ± 0.16 °C and 0.27 ± 0.20 °C for the forehead and wrist, respectively. 95% of the measurements from the forehead model and 86% from the wrist model were within ±0.5 °C of T_re, and 78% (forehead) and 64% (wrist) were within ±0.3 °C. Root Mean Square Deviation (RMSD) values were 0.29 °C and 0.40 °C for the forehead and wrist models, respectively. The developed models show the feasibility to use the Tcore sensor for assessing T_re under exercise-heat conditions. Furthermore, the sensor was found to be adequate for use on the wrist as well, which might be more practical for use in field conditions.

Accuracy of the non-invasive Tcore™ temperature monitoring system to measure body core temperature in abdominal surgery

An accurate determination of body core temperature is crucial during surgery in order to avoid and treat hypothermia, which is associated with poor outcome. In a prospective observational study, we evaluated the suitability of the Tcore™ device (Drägerwerk AG & Co. KGaA, Lübeck, Germany)-a non-invasive thermometer-to accurately determine core body temperature. In patients undergoing surgery for ovarian cancer, core body temperature (CBT) was determined with the Tcore™ sensor attached to the forehead and compared with blood temperature (T_blood) as measured within the femoro-iliacal artery. Both temperatures were recorded every 10 s and the measurement error was calculated. 57,302 data pairs of CBT and T_blood were obtained in 22 patients. In a repeated-measurements version of the Bland and Altman test, a bias of - 0.02 °C and 95% limits of agreement of - 0.48 to 0.44 °C were calculated. In a population analysis, a median absolute error of 0 [- 0.1; + 0.1] °C, a bias of 0 [- 0.276; 0.271] % and an inaccuracy of 0.276 [0.274; 0.354] % was determined. Although the Tcore™ sensor was attached to the frontal skin, it provided an accurate measurement of core body temperature in the investigated intraoperative setting.

Validation of non-invasive brain temperature estimation models during swine therapeutic hypothermia

OBJECTIVES

This paper introduces a mathematical model that can estimate deep brain temperature during therapeutic hypothermia (TH) based on a double sensor method (DSM). Although the cerebral temperature is more important than the non-cerebral core temperature during TH, pulmonary artery (PA), rectal, and esophageal measurements (i.e. the typical core temperature measurement locations) have all been used for target temperature management. This is because there is no safe means of measuring the exact brain temperature.

APPROACH

We applied a double sensor thermometer to the subject's forehead to measure the cerebral temperature non-invasively. Invasive and non-invasive brain temperature readings were acquired for 11 pigs, seven of which were used to develop an optimal model using jackknife resampling and four of which were used to test the model.

MAIN RESULTS

The logit model exhibited the best performance of 0.134 °C root mean square error and a 0.993 Lin's concordance correlation coefficient (CCC). Each test dataset had acceptable results in that each 95% limit of agreement was within the range of clinical acceptance of [-0.5 °C, 0.5 °C]. Three of the four datasets yielded an 'almost perfect' score for Lin's CCC.

SIGNIFICANCE

Only a small number of studies have compared invasively and non-invasively measured brain temperatures, while most previous studies have concentrated on comparison with the core temperature. Furthermore, the possibility of measuring the exact brain temperature safely during TH using a DSM is shown in this work.

Thermometry and interpretation of body temperature

This article reviews the historical development and up-to-date state of thermometric technologies for measuring human body temperature (BT) from two aspects: measurement methodology and significance interpretation. Since the first systematic and comprehensive study on BT and its relation to human diseases was conducted by Wunderlich in the late 19th century, BT has served as one of the most fundamental vital signs for clinical diagnosis and daily healthcare. The physiological implication of BT set point and thermoregulatory mechanisms are briefly outlined. Influential determinants of BT measurement are investigated thoroughly. Three types of BT measurement, i.e., core body temperature, surface body temperature and basal body temperature, are categorized according to its measurement position and activity level. With the comparison of temperature measurement in industrial fields, specialties in technological and biological aspects in BT measurement are mentioned. Methodologies used in BT measurement are grouped into instrumental methods and mathematical methods. Instrumental methods utilize results of BT measurements directly from temperature-sensitive transducers and electronic instrumentations by the combination of actual and predictive measurement, invasive and noninvasive measurement. Mathematical methods use several numerical models, such as multiple regression model, autoregressive model, thermoregulatory mechanism-based model and the Kalman filter-based method to estimate BT indirectly from some relevant vital signs and environmental factors. Thermometry modalities are summarized on the dichotomies into invasive and noninvasive, contact and noncontact, direct and indirect, free and restrained, 1-D and n-D. Comprehensive interpretation of BT has an equal importance as the measurement of BT. Two modes to apply BT are classified into real-time applications and long-term applications. With rapid advancement in IoT infrastructure, big data analytics and AI platforms, prospects for future development in thermometry and interpretation of BT are discussed.

A Smart Pillow for Health Sensing System Based on Temperature and Humidity Sensors

The quality of sleep affects the patient's health, along with the observation of vital life signs such as body temperature and sweat in sleep, is essential in the monitoring of sleep as well as clinical diagnosis. However, traditional methods in recording physiological change amidst sleep is difficult without being intrusive. The smart pillow is developed to provide a relatively easy way to observe one's sleep condition, employing temperature and humidity sensors by implanting them inside the pillow in strategic positions. With the patient's head on the pillow, the roles of sensors are identified as main, auxiliary or environmental temperature, based on the differences of value from three temperature sensors, thus the pattern of sleep can be extracted by statistical analysis, and the body temperature is inferred by a specially designed Fuzzy Logic System if the head-on position is stable for more than 15 min. Night sweat is reported on data from the humidity sensor. Therefore, a cloud-based health-sensing system is built in the smart pillow to collect and analyze data. Experiments from various individuals prove that statistical and inferred results reflect normal and abnormal conditions of sleep accurately. The daily sleeping information of patients from the pillow is helpful in the decision-making of diagnoses and treatment, and users can change their habits of sleep gradually by observing the data with their health professional.

Limb Skin Temperature as a Tool to Predict Orthostatic Instability

Orthostatic instability is one of the main consequences of weightlessness or gravity challenge and plays as well a crucial role in public health, being one of the most frequent disease of aging. Therefore, the assessment of effective countermeasures, or even the possibility to predict, and thus prevent orthostatic instability is of great importance. Heat stress affects orthostatic stability and may lead to impaired consciousness and decrease in cerebral perfusion, specifically during the exposure to G-forces. Conversely, peripheral cooling can prevent orthostatic intolerance – even in normothermic healthy subjects. Indicators of peripheral vasodilation, as elevated skin surface temperatures, may mirror blood decentralization and an increased risk of orthostatic instability. Therefore, the aim of this study was to quantify orthostatic instability risk, by assessing in 20 fighter jet pilot candidates’ cutaneous limb temperatures, with respect to the occurrence of G-force-induced almost loss of consciousness (ALOC), before and during exposure to a push-pull maneuver, i.e., head-down tilt, combined with lower body negative pressure. Peripheral skin temperatures from the upper and lower (both proximal and distal) extremities and core body temperature via heat-flux approach (i.e., the Double Sensor), were continuously measured before and during the maneuver. The 55% of subjects that suffered an ALOC during the procedure had higher upper arm and thigh temperatures at baseline compared to the 45% that remained stable. No difference in baseline core body temperature and distal limbs (both upper and lower) skin temperatures were found between the two groups. Therefore, peripheral skin temperature data could be considered a predicting factor for ALOC, prior to rapid onset acceleration. Moreover, these findings could also find applications in patient care settings such as in intensive care units.

On the use of wearable physiological monitors to assess heat strain during occupational heat stress

Workers in many industries are required to perform arduous work in high heat-stress conditions, which can lead to rapid increases in body temperature that elevate the risk of heat-related illness and even death. Traditionally, effort to mitigate work-related heat injury has been directed toward the assessment of environmental heat stress (e.g., wet-bulb globe temperature), rather than toward the associated physiological strain responses (e.g., heart rate and skin and core temperatures). However, because a worker’s physiological response to a given heat stress is modified independently by inter-individual factors (e.g., age, sex, chronic disease, others) and intra-individual factors both within (e.g., medication use, fitness, acclimation and hydration state, others) and beyond (e.g., shift duration, illness, others) the worker’s control, it becomes challenging to protect workers on an individual basis from heat-related injury without assessing those physiological responses. Recent advancements in wearable technology have made it possible to monitor one or more physiological indices of heat strain. Nonetheless, information on the utility of the wearable systems available for assessing occupational heat strain is unavailable. This communication is therefore directed toward identifying the physiological indices of heat strain that may be quantified in the workplace and evaluating the wearable monitoring systems available for assessing those responses. Finally, emphasis is placed on the barriers associated with implementing these devices to assist in mitigating work-related heat injury. This information is fundamental for protecting worker health and could also be utilized to prevent heat illnesses in vulnerable people during leisure or athletic activities.

Wearable physiological monitoring for human thermal-work strain optimization

Safe performance limits of soldiers and athletes have typically relied on predictive work-rest models of ambient conditions, average work intensity, and characteristics of the population. Bioengineering advances in noninvasive sensor technologies, including miniaturization, reduced cost, power requirements, and comfort, now make it possible to produce individual predictions of safe thermal-work limits. These precision medicine assessments depend on the development of thoughtful algorithms based on physics and physiology. Both physiological telemetry and thermal-strain indexes have been available for >50 years, but greater computing power and better wearable sensors now make it possible to provide actionable information at the individual level. Core temperature can be practically estimated from time series heart rate data and, using an adaptive physiological strain index, provides meaningful predictions of safe work limits that cannot be predicted from only core temperature or heart rate measurements. Early adopters of this technology include specialized occupations where individuals operate in complete encapsulation such as chemical protective suits. Emerging technologies that focus on heat flux measurements at the skin show even greater potential for estimating thermal-work strain using a parsimonious sensor set. Applications of these wearable technologies include many sports and military training venues where inexperienced individuals can learn effective work pacing strategies and train to safe personal limits. The same strategies can also provide a technologically based performance edge for experienced workers and athletes faced with novel and nonintuitive physiological challenges, such as health care providers in full protective clothing treating Ebola patients in West Africa in 2014.

NEW & NOTEWORTHY This mini-review details how the application of computational techniques borrowed from signal processing and control theory can provide meaningful advances for the applied physiological problem of real-time thermal-work strain monitoring. The work examines the development of practical core body temperature estimation techniques and how these can be used in combination with current and updated thermal-work strain indexes to provide objective state assessments and to optimize work rest schedules for a given task.

Increased core body temperature in astronauts during long-duration space missions

Humans’ core body temperature (CBT) is strictly controlled within a narrow range. Various studies dealt with the impact of physical activity, clothing, and environmental factors on CBT regulation under terrestrial conditions. However, the effects of weightlessness on human thermoregulation are not well understood. Specifically, studies, investigating the effects of long-duration spaceflight on CBT at rest and during exercise are clearly lacking. We here show that during exercise CBT rises higher and faster in space than on Earth. Moreover, we observed for the first time a sustained increased astronauts’ CBT also under resting conditions. This increase of about 1 °C developed gradually over 2.5 months and was associated with augmented concentrations of interleukin-1 receptor antagonist, a key anti-inflammatory protein. Since even minor increases in CBT can impair physical and cognitive performance, both findings have a considerable impact on astronauts’ health and well-being during future long-term spaceflights. Moreover, our findings also pinpoint crucial physiological challenges for spacefaring civilizations, and raise questions about the assumption of a thermoregulatory set point in humans, and our evolutionary ability to adapt to climate changes on Earth.

Umbilical temperature correlation with core and skin temperatures at rest, in the heat and during physical activity

PURPOSE

to determine the correlation of umbilical temperatures (T_umb) with simultaneously recorded chest wall temperature (T_chest) and rectal temperature (T_rectal) in adults during rest, heat exposure and exercise.

METHODS

A total of 28 healthy men, wearing different types of clothing (athletic garb, a spandex full body heating garment, firefighter bunker gear) had average and peak umbilical, chest wall and rectal temperature measurements taken during sedentary temperature stabilisation stages, heat exposure periods and active exercise phases.

RESULTS

Curvilinear relationships were noted between T_chest and T_umb compared with T_rectal and their association became noticeably positive and linear at approximately 35.5 °C. Polynomial regression analysis of T_rectal with linear and quadratic forms of T_chest and T_umb indicated an overall R² of 0.657 and 0.767, respectively. Bivariate analysis of a restricted data set (where T_chest and T_umb ≥35.5°), indicated that T_umb was significantly associated with T_rectal (r_average = 0.710, p <0.001; r_peak  = 0.841, p <0.001) and T_chest was also significantly associated with T_rectal, but less so (r_average = 0.570, p <0.001; r_peak = 0.699, p <0.001).

CONCLUSIONS

the umbilicus offers a non-invasive, peripheral site for measurement of temperature that more closely correlated with body core temperature than T_chest when core temperature was ≥35.5 °C.

Circadian rhythms in bed rest: Monitoring core body temperature via heat-flux approach is superior to skin surface temperature

Continuous recordings of core body temperature (CBT) are a well-established approach in describing circadian rhythms. Given the discomfort of invasive CBT measurement techniques, the use of skin temperature recordings has been proposed as a surrogate. More recently, we proposed a heat-flux approach (the so-called Double Sensor) for monitoring CBT. Studies investigating the reliability of the heat-flux approach over a 24-hour period, as well as comparisons with skin temperature recordings, are however lacking. The first aim of the study was therefore to compare rectal, skin, and heat-flux temperature recordings for monitoring circadian rhythm. In addition, to assess the optimal placement of sensor probes, we also investigated the effect of different anatomical measurement sites, i.e. sensor probes positioned at the forehead vs. the sternum. Data were collected as part of the Berlin BedRest study (BBR2-2) under controlled, standardized, and thermoneutral conditions. 24-hours temperature data of seven healthy males were collected after 50 days of -6° head-down tilt bed-rest. Mean Pearson correlation coefficients indicated a high association between rectal and forehead temperature recordings (r > 0.80 for skin and Double Sensor). In contrast, only a poor to moderate relationship was observed for sensors positioned at the sternum (r = -0.02 and r = 0.52 for skin and Double Sensor, respectively). Cross-correlation analyses further confirmed the feasibility of the forehead as a preferred monitoring site. The phase difference between forehead Double Sensor and rectal recordings was not statistically different from zero (p = 0.313), and was significantly smaller than the phase difference between forehead skin and rectal temperatures (p = 0.016). These findings were substantiated by cosinor analyses, revealing significant differences for mesor, amplitude, and acrophase between rectal and forehead skin temperature recordings, but not between forehead Double Sensor and rectal temperature measurements. Finally, Bland-Altman analysis indicated narrower limits of agreement for rhythm parameters between rectal and Double Sensor measurements compared to between rectal and skin recordings, irrespective of the measurement site (i.e. forehead, sternum). Based on these data we conclude that (1) Double Sensor recordings are significantly superior to skin temperature measurements for non-invasively assessing the circadian rhythm of rectal temperature, and (2) temperature rhythms from the sternum are less reliable than from the forehead. We suggest that forehead Double Sensor recordings may provide a surrogate for rectal temperature in circadian rhythm research, where constant routine protocols are applied. Future studies will be needed to assess the sensor's ecological validity outside the laboratory under changing environmental and physiological conditions.

Evaluation of physiological strain in hot work areas using thermal imagery

BACKGROUND

Monitoring core body temperature to identify heat strain in workers engaged in hot work in heat stress environments is intrusive and expensive. Nonintrusive, inexpensive methods are needed to calculate individual Physiological Strain Index (PSI).

OBJECTIVE

Thermal imaging and heart rate monitoring were used in this study to calculate Physiological Strain Index (PSI) from thermal imaging temperatures of human subjects wearing thermal protective garments during recovery from hot work.

METHODS

Ten male subjects were evaluated for physiological strain while participating in hot work. Thermal images of the head and neck were captured with a high-resolution thermal imaging camera concomitant with measures of gastrointestinal and skin temperature. Lin's concordance correlation coefficient (rho_c), Pearson's coefficient (r) and bias correction factor (C-b) were calculated to compare thermal imaging based temperatures to gastrointestinal temperatures. Calculations of PSI based thermal imaging recorded temperatures were compared to gastrointestinal based PSI.

RESULTS

Participants reached a peak PSI of 5.2, indicating moderate heat strain. Sagittal measurements showed low correlation (rho_c=0.133), moderate precision (r=0.496) and low accuracy (C_b=0.269) with gastrointestinal temperature. Bland-Altman plots of imaging measurements showed increasing agreement as gastrointestinal temperature rose; however, the Limits of Agreement (LoA) fell outside the ±0.25C range of clinical significance. Bland-Altman plots of PSI calculated from imaging measurements showed increasing agreement as gastrointestinal temperature rose; however, the LoA fell outside the ±0.5 range of clinical significance.

CONCLUSION

Results of this study confirmed previous research showing thermal imagery is not highly correlated to body core temperature during recovery from moderate heat strain in mild ambient conditions. Measurements display a trend toward increasing correlation at higher body core temperatures. Accuracy was not sufficient at mild to moderate heat strain to allow calculation of individual physiological stress.

Comparison of estimated core body temperature measured with the BioHarness and rectal temperature under several heat stress conditions

Monitoring and measuring core body temperature is important to prevent or minimize physiological strain and cognitive dysfunction for workers such as first responders (e.g., firefighters) and military personnel. The purpose of this study is to compare estimated core body temperature (Tco-est), determined by heart rate (HR) data from a wearable chest strap physiology monitor, to standard rectal thermometry (Tre) under different conditions.  Tco-est and Tre measurements were obtained in thermoneutral and heat stress conditions (high temperature and relative humidity) during four different experiments including treadmill exercise, cycling exercise, passive heat stress, and treadmill exercise while wearing personal protective equipment (PPE).  Overall, the mean Tco-est did not differ significantly from Tre across the four conditions. During exercise at low-moderate work rates under heat stress conditions, Tco-est was consistently higher than Tre at all-time points. Tco-est underestimated temperature compared to Tre at rest in heat stress conditions and at a low work rate under heat stress while wearing PPE. The mean differences between the two measurements ranged from -0.1 ± 0.4 to 0.3 ± 0.4°C and Tco-est correlated well with HR (r = 0.795 - 0.849) and mean body temperature (r = 0.637 - 0.861).  These results indicate that, the comparison of Tco-est to Tre may result in over- or underestimation which could possibly lead to heat-related illness during monitoring in certain conditions. Modifications to the current algorithm should be considered to address such issues.

Use of finite element analysis to optimize probe design for double sensor method-based thermometer

Body temperature is an essential vital sign for assessing physiological functions. The double sensor method-based thermometer is a promising technology that may be applicable to body temperature monitoring in daily life. It continuously estimates deep tissue temperature from the intact skin surface. Despite its considerable potential for monitoring body temperature, its key design features have not been investigated. In this study, we considered four design factors: the cover material, insulator material, insulator radius, and insulator height. We also evaluated their effects on the performance of the double sensor thermometer in terms of accuracy, initial waiting time, and the ability to track changes in body temperature. The probe material and size influenced the accuracy and initial waiting time. Finite element analysis revealed that four thermometers of different sizes composed of an aluminum cover and foam insulator provided high accuracy (<0.1°C) under various ambient temperatures and blood perfusion rates: R=20mm, H=5mm; R=15mm, H=10mm; R=20mm, H=10mm; and R=15mm, H=15mm. The initial waiting time was approximately 10min with almost the same traceability of temperature change. Our findings may provide thermometer manufacturers with new insights into probe design and help them fabricate thermometers optimized for specific applications.

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 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.

Temperature Measurement Inside Protective Headgear: Comparison With Core Temperatures and Indicators of Physiological Strain During Exercise in a Hot Environment

Non-invasive temperature monitoring with a sensor inside protective headgear may be effective in detecting temperatures that are associated with heat illness. The purpose was to establish the relationship between in-hardhat temperatures (Tih) and core temperature (Tc) as measured by rectal (Tre) and esophageal (Tes) probes. Thirty males (age 24.57 ± 4.32 yrs.) completed two trials: continuous submaximal exercise (CSE) and a series of high intensity 30-s sprints (HIE) with a one-minute rest between each. Exercise in both conditions was in a 36(°)C environment (40% RH) while wearing a standard hardhat with sensors mounted on the forehead that were monitored remotely. Exercise continued until voluntary termination or until Tc reached 39.5(°)C. Temperatures, heart rate, cardiorespiratory, and perceptual responses were monitored throughout. A physiological strain index (PSI) was calculated from Tc and HR. The final temperatures in the CSE condition were 38.77 ± 0.41, 38.90 ± 0.49 and 39.29 ± 0.58(°)C and in the HIE condition, final temperatures were 38.76 ± 0.37, 38.91 ± 0.47, and 39.19 ± 0.57 f (o)C for Tih, Tre, and Tes, respectively. The PSI in CSE was 9.62 ± 062, 9.18 ± 1.11, and 10.04 ± 1.05, and in the HIE condition 9.67 ± 068, 9.29 ± 0.99. and 9.86 ± 1.02 based on Tih, Tre and Tes, respectively. The general agreement between the Tih and other temperature measures along with the consistency as indicated by a low coefficient of variation (approx. 1%) in the recordings of the Tih sensors at the point of termination suggest that this device, or similar devices, may have application as a warning system for impending heat-related problems.

Evaluation of structural and thermophysical effects on the measurement accuracy of deep body thermometers based on dual-heat-flux method

To help pave a path toward the practical use of continuous unconstrained noninvasive deep body temperature measurement, this study aims to evaluate the structural and thermophysical effects on measurement accuracy for the dual-heat-flux method (DHFM). By considering the thermometer's height, radius, conductivity, density and specific heat as variables affecting the accuracy of DHFM measurement, we investigated the relationship between those variables and accuracy using 3-D models based on finite element method. The results of our simulation study show that accuracy is proportional to the radius but inversely proportional to the thickness of the thermometer when the radius is less than 30.0mm, and is also inversely proportional to the heat conductivity of the heat insulator inside the thermometer. The insights from this study would help to build a guideline for design, fabrication and optimization of DHFM-based thermometers, as well as their practical use.

Thermoregulatory modeling use and application in the military workforce

Thermoregulatory models have been used in the military to quantify probabilities of individuals' thermal-related illness/injury. The uses of the models have diversified over the past decade. This paper revisits an overall view of selected thermoregulatory models used in the U.S. military and provides examples of actual practical military applications: 1) the latest military vehicle designed with armor and blast/bulletproof windows was assessed to predict crews' thermal strains levels inside vehicles under hot environment (air temperature [Ta]: 29-43 °C, dew point: 13 °C); 2) a military working dog (MWD) model was developed by modifying existing human thermoregulatory models with canine physical appearance and physiological mechanisms; 3) thermal tolerance range of individuals from a large military group (n = 100) exposed to 35 °C/40% relative humidity were examined using thermoregulatory modeling and multivariate statistical analyses. Model simulation results assist in the decisions for the strategic planning and preventions of heat stress.

Prediction of human core body temperature using non-invasive measurement methods

The measurement of core body temperature is an efficient method for monitoring heat stress amongst workers in hot conditions. However, invasive measurement of core body temperature (e.g. rectal, intestinal, oesophageal temperature) is impractical for such applications. Therefore, the aim of this study was to define relevant non-invasive measures to predict core body temperature under various conditions. We conducted two human subject studies with different experimental protocols, different environmental temperatures (10 °C, 30 °C) and different subjects. In both studies the same non-invasive measurement methods (skin temperature, skin heat flux, heart rate) were applied. A principle component analysis was conducted to extract independent factors, which were then used in a linear regression model. We identified six parameters (three skin temperatures, two skin heat fluxes and heart rate), which were included for the calculation of two factors. The predictive value of these factors for core body temperature was evaluated by a multiple regression analysis. The calculated root mean square deviation (rmsd) was in the range from 0.28 °C to 0.34 °C for all environmental conditions. These errors are similar to previous models using non-invasive measures to predict core body temperature. The results from this study illustrate that multiple physiological parameters (e.g. skin temperature and skin heat fluxes) are needed to predict core body temperature. In addition, the physiological measurements chosen in this study and the algorithm defined in this work are potentially applicable as real-time core body temperature monitoring to assess health risk in broad range of working conditions.

Leveraging knowledge from physiological data: on-body heat stress risk prediction with sensor networks

The paper demonstrates that wearable sensor systems, coupled with real-time on-body processing and actuation, can enhance safety for wearers of heavy protective equipment who are subjected to harsh thermal environments by reducing risk of Uncompensable Heat Stress (UHS). The work focuses on Explosive Ordnance Disposal operatives and shows that predictions of UHS risk can be performed in real-time with sufficient accuracy for real-world use. Furthermore, it is shown that the required sensory input for such algorithms can be obtained with wearable, non-intrusive sensors. Two algorithms, one based on Bayesian nets and another on decision trees, are presented for determining the heat stress risk, considering the mean skin temperature prediction as a proxy. The algorithms are trained on empirical data and have accuracies of 92.1±2.9% and 94.4±2.1%, respectively when tested using leave-one-subject-out cross-validation. In applications such as Explosive Ordnance Disposal operative monitoring, such prediction algorithms can enable autonomous actuation of cooling systems and haptic alerts to minimize casualties.