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人类在高温环境下运动:汗液模型综述及与近期实验数据集的比较

Humans exercising in the heat: A review on sweat models and a comparison to recent experimental datasets.

作者信息

de Korver Robin, Kingma Boris R M, Havenith George, Kuklane Kalev, Kenny Glen P, Meade Robert D, Frijns Arjan J H

机构信息

Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Department of Human Performance, The Netherlands Organization for Applied Scientific Research (TNO), Soesterberg, The Netherlands.

出版信息

Temperature (Austin). 2025 Jun 5;12(3):209-230. doi: 10.1080/23328940.2025.2508534. eCollection 2025.

Abstract

Sweating is a vital thermoregulatory mechanism in humans for maintaining thermal balance during exercise and exposure to hot environments. The development of models that predict sweat rate based on body temperature has been ongoing for over half a century. Here, we compared predicted water loss rates (WLR) from these models to actual observations collected during 780 participant-exposures in three independent laboratory-based experiments. In these experiments, male participants aged 19-50 years cycled or walked at various intensities (metabolic heat productions between 200 and 970 W), in air temperatures ranging from -40°C to 50°C, relative humidities (14% to 95%), and air velocities (<0.2 to 10 m/s), while wearing different clothing ensembles (thermal insulation 0.20 to 3.75 clo). The models' performances were evaluated by the coefficient of determination (R) and Root Mean Square Error (RMSE). Performance varied greatly with a maximum R value of 0.5 and RMSE values ranging from 10.4 to 4.9 g/min. Models with a lower sweat onset core temperature setpoint performed better and most models generally underestimated the water loss at higher WLR. Optimization of the core and skin temperature setpoints suggests preferred core temperature setpoints within a narrow range (36.2°C to 36.6°C). Even with optimized inputs, R values were around 0.5, meaning only 50% of the variance in observed WLR was explained by the models. Better model consideration of relations between body temperature and sweat rate, and the incorporation of non-thermal exercise-induced sweat promotion, may reduce model underpredictions at higher exercise intensities.

摘要

出汗是人体重要的体温调节机制,可在运动及暴露于炎热环境时维持热平衡。基于体温预测出汗率的模型已发展了半个多世纪。在此,我们将这些模型预测的失水率(WLR)与在三个独立的实验室实验中780名参与者暴露期间收集的实际观测值进行了比较。在这些实验中,年龄中,19至50岁的男性参与者在-40°C至50°C的气温、14%至95%的相对湿度以及<0.2至10 m/s的风速条件下,以不同强度(代谢产热在200至970 W之间)进行骑车或步行运动,同时穿着不同的服装组合(隔热值为0.20至3.75 clo)。通过决定系数(R)和均方根误差(RMSE)对模型的性能进行评估。模型性能差异很大,R值最高为0.5,RMSE值在10.4至4.9 g/min之间。出汗起始核心体温设定点较低的模型表现更好,大多数模型在较高WLR时通常低估了失水量。核心温度和皮肤温度设定点的优化表明,在较窄范围内(36.2°C至36.6°C)存在优选的核心温度设定点。即使输入经过优化,R值仍约为0.5,这意味着模型仅解释了观测到的WLR中50%的方差。更好地考虑体温与出汗率之间的关系,并纳入非热运动诱导的出汗促进因素,可能会减少模型在较高运动强度下的预测不足。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0773/12416190/2e438c6412ab/KTMP_A_2508534_F0001_OC.jpg

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