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Validation of an individualised model of human thermoregulation for predicting responses to cold air

机译:验证人的温度调节个体模型以预测对冷空气的反应

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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.
机译:人类体温调节的大多数计算机模型都是基于人群的。在这里,我们个性化了Fiala模型[Fiala等。 (2001)Int J Biometeorol 45:143-159],有关人体测量学,体脂和代谢率。将适应的多节段体温调节模型的预测与测得的个体皮肤温度进行比较。来自两个实验的数据用于研究对动态皮肤温度反应的影响,在该实验中,斜躺的受试者突然暴露于轻度至中度的寒冷环境中。通过三室法结合水下称量和氘稀释法测量人体脂肪。代谢率通过间接量热法测定。在实验1中,冷暴露期间,预计和测得的平均皮肤温度之间的偏差(均值差)从1.8摄氏度降低到-0.15摄氏度。平均差的标准偏差保持相同的幅度(从0.7摄氏度到0.9摄氏度)。在实验2中,皮肤温度的偏差从使用标准模型的2.0 +/- 1.09摄氏度更改为使用模型中的各个特征的1.3 +/- 0.93摄氏度。个体特征的包含因此改善了个体的预测,并导致明显较小的系统误差。但是,个人对感冒反应的大部分差异仍无法解释。讨论了通过包含更多主题特征(即人体脂肪分布,体形)以及对(皮肤)血液灌注水平和控制功能的模型改进而实现的模型的进一步改进。

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