While numerous physical skin models have been reported, most developments are research field-specific and based on trial-and-error methods. As the complexity of advanced measurement techniques increases, new interdisciplinary approaches are needed in future to achieve refined models which realistically simulate multiple properties of human skin.

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.

Background: Skin temperature (Tskin) is commonly measured using Tskin sensors affixed directly to the skin surface, although the influence of setup variables on the measured outcome requires clarification.Objectives: The two distinct objectives of this systematic review were (1) to examine measurements from contact Tskin sensors considering equilibrium temperature and temperature disturbance, sensor attachments, pressure, environmental temperature, and sensor type, and (2) to characterise the contact Tskin sensors used, conditions of use, and subsequent reporting in studies investigating sports, exercise, and other physical activity.Data sources and study selection: For the measurement comparison objective, Ovid Medline and Scopus were used (1960 to July 2016) and studies comparing contact Tskin sensor measurements in vivo or using appropriate physical models were included. For the survey of use, Ovid Medline was used (2011 to July 2016) and studies using contact temperature sensors for the measurement of human Tskin in vivo during sport, exercise, and other physical activity were included.Study appraisal and synthesis methods: For measurement comparisons, assessments of risk of bias were made according to an adapted version of the Cochrane Collaboration's risk of bias tool. Comparisons of temperature measurements were expressed, where possible, as mean difference and 95% limits of agreement (LoA). Meta-analyses were not performed due to the lack of a common reference condition. For the survey of use, extracted information was summarised in text and tabular form.Results: For measurement comparisons, 21 studies were included. Results from these studies indicated minor (<0.5°C) to practically meaningful (>0.5°C) measurement bias within the subgroups of attachment type, applied pressure, environmental conditions, and sensor type. The 95% LoA were often within 1.0°C for in vivo studies and 0.5°C for physical models. For the survey of use, 172 studies were included. Details about Tskin sensor setup were often poorly reported and, from those reporting setup information, it was evident that setups widely varied in terms of type of sensors, attachments, and locations used.Conclusions: Setup variables and conditions of use can influence the measured temperature from contact Tskin sensors and thus key setup variables need to be appropriately considered and consistently reported.

Real evaporative cooling efficiency, the ratio of real evaporative heat loss to evaporative cooling potential, is an important parameter to characterize the real cooling benefit for the human body. Previous studies on protective clothing showed that the cooling efficiency decreases with increasing distance between the evaporation locations and the human skin. However, it is still unclear how evaporative cooling efficiency decreases as the moisture is transported from the skin to the clothing layer. In this study, we performed experiments with a sweating torso manikin to mimic three different phases of moisture absorption in one-layer tight-fitting sportswear. Clothing materials Coolmax(®) (CM; INVISTA, Wichita, Kansas, USA; 100%, profiled cross-section polyester fiber), merino wool (MW; 100%), sports wool (SW; 50% wool, 50% polyester), and cotton (CO; 100%) were selected for the study. The results demonstrated that, for the sportswear materials tested, the real evaporative cooling efficiency linearly decreases with the increasing ratio of moisture being transported away from skin surface to clothing layer (adjusted R(2) >0.97). In addition, clothing fabric thickness has a negative effect on the real evaporative cooling efficiency. Clothing CM and SW showed a good ability in maintaining evaporative cooling efficiency. In contrast, clothing MW made from thicker fabric had the worst performance in maintaining evaporative cooling efficiency. It is thus suggested that thin fabric materials such as CM and SW should be used to manufacture one-layer tight-fitting sportswear.

We conclude that a contraction in PV does not negatively affect t lim and that rhEPO improves t lim by additional, non-hematopoietic factors.