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耳模内置传感器测量耳道温度的局限性。

Limitations of temperature measurement in the aural canal with an ear mould integrated sensor.

机构信息

TNO, Human Performance, PO Box 23, 3769 ZG, Soesterberg, The Netherlands.

出版信息

Physiol Meas. 2011 Sep;32(9):1403-16. doi: 10.1088/0967-3334/32/9/004. Epub 2011 Jul 26.

DOI:10.1088/0967-3334/32/9/004
PMID:21788686
Abstract

Aural canal temperature measurement using an ear mould integrated sensor (T(ac)) might be a method suited for continuous non-invasive core temperature estimation in operational settings. We studied the effect of ambient temperature, wind and high intensity exercise on T(ac) and its ability to predict esophageal (T(es)) and rectal temperatures (T(re)). Seven subjects performed a protocol of rest at 21, 10 and 30 °C, followed by exercise and recovery at 30 °C. The subjects performed the protocol twice: with and without face-wind from halfway through the 30 °C rest period. Extra auricle insulation was applied at one side. Ambient temperature changes affected T(ac) significantly, while T(es) and T(re) remained stable. Insulating the auricle reduced but did not abolish this effect. Wind had an immediate cooling effect on T(ac) independent of auricle insulation. During exercise and recovery in 30 °C, T(ac) provided acceptable group predictions of T(re) in trials without wind (bias: -0.66 ± 0.21 °C covered, -1.20 ± 0.15 °C uncovered). Bias was considerably higher with wind, but variability was similar (-1.73 ± 0.11 °C covered, -2.49 ± 0.04 °C uncovered). Individual predictions of T(es) and T(re) showed more variation, especially with wind. We conclude that T(ac) may be used for core temperature assessment of groups in warm and stable conditions.

摘要

使用集成传感器的耳道温度测量(T(ac))可能是一种适合在操作环境中连续进行无创核心温度估计的方法。我们研究了环境温度、风和高强度运动对 T(ac)的影响,以及它预测食管(T(es))和直肠温度(T(re))的能力。七名受试者在 21、10 和 30°C 下进行休息方案,然后在 30°C 下进行运动和恢复。受试者进行了两次方案:一次是在 30°C 休息期间中途有风,另一次没有。一侧额外的耳廓隔热。环境温度变化对 T(ac)有显著影响,而 T(es)和 T(re)保持稳定。隔热耳廓减少了这种影响,但没有消除。风对 T(ac)有即时冷却作用,与耳廓隔热无关。在 30°C 下进行运动和恢复时,T(ac)在没有风的情况下提供了可接受的 T(re)组预测(偏差:-0.66±0.21°C 覆盖,-1.20±0.15°C 未覆盖)。有风时偏差要高得多,但变异性相似(-1.73±0.11°C 覆盖,-2.49±0.04°C 未覆盖)。T(es)和 T(re)的个体预测显示出更多的变化,尤其是有风时。我们得出结论,T(ac)可用于在温暖稳定的条件下评估群体的核心温度。

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