Evaluation of individual thermal sensation at raised indoor temperatures based on skin temperature

Evaluation of individual thermal sensation at raised indoor temperatures based on skin temperature
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根据皮肤温度评估室内温度升高时的个人热感觉

DOI:
10.1016/j.buildenv.2020.107486
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发表时间:
2021-01
影响因子:
7.4
通讯作者:
Y. Deng
Y. Deng
中科院分区:
工程技术1区
文献类型:
--
作者:
W. Liu;X. Tian;D. Yang;Y. Deng

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在本研究中,我们进一步探讨皮肤温度是否也可以评估个人的热感觉作为一个有效的生理指标,而以前的研究没有得出广泛的概括性结论,在高温下。气候控制实验包括26、30、33、37和39 °C五个温度水平,50%和70%两个相对湿度水平,以及轻度和中度两个活动水平,其中估计的平均代谢率分别为58 W/m2和165 W/m2。136名长期生活在湿热环境中的健康受试者参加了这些实验。在实验期间,记录热感觉、舒适性和可接受性的评级,连续监测局部皮肤温度,并计算五个平均皮肤温度。利用Fisher判别分析对皮肤温度进行热感觉建模,得到不同热感觉类别对应的局部皮肤温度和平均皮肤温度阈值,验证模型评估的准确性。结果表明,在超出正常温度范围的30-39 ℃高温下,皮肤温度也可以预测热感觉。所提出的评估模型显示出较高的准确性来预测“热/非常热”的类别,和高达93%的准确性预测热感觉从手腕皮肤温度。此外,对高温和高湿度的热适应会影响从皮肤温度预测“热/非常热”类别的准确性。研究结果为高温下人体安全风险预警提供了重要依据。
In this study, we further investigate whether skin temperature can also assess individual thermal sensation as an effective physiological index while previous studies did not draw broadly generalizable conclusions at high temperature. The climate-controlled experiments include five temperature levels of 26, 30, 33, 37 and 39 °C, two relative humidity levels of 50% and 70%, and two activity levels with light and moderate and in which the estimated average metabolic rate were respectively 58 W/m2and 165 W/m2. A total of 136 healthy subjects who lived in hot-humid climate for a long time participated in these experiments. During the experiments, the ratings of thermal sensation, comfort and acceptability were documented, local skin temperatures were continuously monitored, and five mean skin temperatures were calculated. Using Fisher discriminant analysis to model thermal sensation from skin temperature, then obtaining the thresholds of local and mean skin temperatures corresponding to different thermal sensation categories, and finally verifying the accuracy of the models assessment. The results show that the skin temperature can also predict thermal sensation at high temperatures of 30–39 °C beyond the range of normal temperatures. The proposed evaluation models show a high accuracy to predict the “hot/very hot” category, and up to 93% accuracy of predicting thermal sensation from wrist skin temperature. Additionally, thermal adaptation to high temperature and humidity can affect the prediction accuracy of “hot/very hot” category from skin temperature. The results of this study provide an important basis for early warning when human's safety risk occurs under high temperatures.
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