Department of Mechanical Engineering, Eindhoven University of Technology, the Netherlands.
Department of Mechanical Engineering, Eindhoven University of Technology, the Netherlands; TNO, The Netherlands Organization for Applied Scientific Research, Unit Defense, Safety & Security, Soesterberg, the Netherlands.
J Therm Biol. 2019 Aug;84:439-450. doi: 10.1016/j.jtherbio.2019.07.033. Epub 2019 Jul 29.
The quality of local skin temperature prediction by thermophysiological models depends on the local skin blood flow (SBF) control functions. These equations were derived for low activity levels (0.8-1met) and mostly in sitting or supine position. This study validates and discusses the prediction of foot SBF during activities of 1-3met in male and females, and the effect on the foot skin temperature prediction (ΔT) using the thermophysiological simulation model ThermoSEM. The SBF at the foot was measured for ten male and ten female human subjects at baseline and during three activities (sitting, walking at 1km/h, preferred walking around 3km/h). Additional measurements included the energy expenditure, local skin temperatures (T), environmental conditions and body composition. Measured, normalized foot SBF is 2-8 times higher than the simulated SBF during walking sessions. Also, SBF increases are significantly higher in females vs. males (preferred walking: 4.8±1.5 versus 2.7±1.4, P < 0.05). The quality of ΔT using the simulated foot SBF is poor (median deviation is -4.8°C, maximumumdeviationis-6°C). Using the measured SBF in ThermoSEM results in an improved local skin temperature prediction (new maximum deviation is -3.3°C). From these data a new SBF model was developed that includes the walking activity level and gender, and improves SBF prediction and ΔT of the thermophysiological model. Accurate SBF and local skin temperature predictions are beneficial in optimizing thermal comfort simulations in the built environment, and might also be applied in sport science or patient's temperature management.
局部皮肤温度预测的质量取决于生理热模型的局部皮肤血流 (SBF) 控制功能。这些方程是为低活动水平（0.8-1met）推导的，主要是在坐姿或仰卧位。本研究验证和讨论了男性和女性在 1-3met 活动期间足部 SBF 的预测，以及使用生理热模拟模型 ThermoSEM 对足部皮肤温度预测 (ΔT) 的影响。在基线和三种活动（坐姿、以 1km/h 的速度行走、3km/h 的速度行走）期间，对 10 名男性和 10 名女性人体受试者的足部 SBF 进行了测量。额外的测量包括能量消耗、局部皮肤温度 (T)、环境条件和身体成分。测量的、归一化的足部 SBF 在行走过程中比模拟的 SBF 高 2-8 倍。此外，女性的 SBF 增加明显高于男性（首选行走：4.8±1.5 对 2.7±1.4，P < 0.05）。使用模拟的足部 SBF 进行的 ΔT 质量较差（中位数偏差为-4.8°C，最大偏差为-6°C）。在 ThermoSEM 中使用测量的 SBF 可改善局部皮肤温度预测（新的最大偏差为-3.3°C）。从这些数据中开发了一种新的 SBF 模型，该模型包含行走活动水平和性别，并提高了 SBF 预测和生理热模型的 ΔT。准确的 SBF 和局部皮肤温度预测有助于优化建筑环境中的热舒适模拟，也可应用于运动科学或患者的体温管理。
