van Marken Lichtenbelt Wouter D, Frijns Arjan J H, van Ooijen Marieke J, Fiala Dusan, Kester Arnold M, van Steenhoven Anton A
Department of Human Biology, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.
Int J Biometeorol. 2007 Jan;51(3):169-79. doi: 10.1007/s00484-006-0060-9. Epub 2006 Nov 10.
Most computer models of human thermoregulation are population based. Here, we individualised the Fiala model [Fiala et al. (2001) Int J Biometeorol 45:143-159] with respect to anthropometrics, body fat, and metabolic rate. The predictions of the adapted multisegmental thermoregulatory model were compared with measured skin temperatures of individuals. Data from two experiments, in which reclining subjects were suddenly exposed to mild to moderate cold environmental conditions, were used to study the effect on dynamic skin temperature responses. Body fat was measured by the three-compartment method combining underwater weighing and deuterium dilution. Metabolic rate was determined by indirect calorimetry. In experiment 1, the bias (mean difference) between predicted and measured mean skin temperature decreased from 1.8 degrees C to -0.15 degrees C during cold exposure. The standard deviation of the mean difference remained of the same magnitude (from 0.7 degrees C to 0.9 degrees C). In experiment 2 the bias of the skin temperature changed from 2.0+/-1.09 degrees C using the standard model to 1.3+/-0.93 degrees C using individual characteristics in the model. The inclusion of individual characteristics thus improved the predictions for an individual and led to a significantly smaller systematic error. However, a large part of the discrepancies in individual response to cold remained unexplained. Possible further improvements to the model accomplished by inclusion of more subject characteristics (i.e. body fat distribution, body shape) and model refinements on the level of (skin) blood perfusion, and control functions, are discussed.
大多数人体体温调节的计算机模型都是基于群体的。在此，我们针对人体测量学、体脂和代谢率对菲亚拉模型[菲亚拉等人（2001年）《国际生物气象学杂志》45:143 - 159]进行了个体化处理。将适配后的多节段体温调节模型的预测结果与个体的实测皮肤温度进行了比较。来自两项实验的数据被用于研究对动态皮肤温度反应的影响，在这两项实验中，躺着的受试者突然暴露于轻度至中度寒冷的环境条件下。体脂通过结合水下称重和氘稀释的三室法进行测量。代谢率通过间接量热法测定。在实验1中，寒冷暴露期间预测的平均皮肤温度与实测平均皮肤温度之间的偏差（平均差值）从1.8摄氏度降至 - 0.15摄氏度。平均差值的标准差保持在相同幅度（从0.7摄氏度至0.9摄氏度）。在实验2中，皮肤温度的偏差从使用标准模型时的2.0±1.09摄氏度变为使用模型中的个体特征时的1.3±0.93摄氏度。因此，纳入个体特征改善了对个体的预测，并导致系统误差显著减小。然而，个体对寒冷反应的大部分差异仍无法解释。讨论了通过纳入更多受试者特征（即体脂分布、体型）以及在（皮肤）血液灌注和控制功能层面进行模型优化对该模型可能的进一步改进。
