a Department of Mathematics and Industrial Engineering , Polytechnique Montréal , Montréal , Canada.
b Ministère des Forêts, de la Faune et des Parcs , Direction de la recherche forestière , Québec , Canada.
Ergonomics. 2019 Aug;62(8):1066-1085. doi: 10.1080/00140139.2019.1588386. Epub 2019 Apr 9.
The heart rate thermal component ( ) can increase with body heat accumulation and lead to work metabolism (WM) overestimation. We used two methods (VOGT and KAMP) to assess of 35 forest workers throughout their work shifts, then compared at work and at rest using limits of agreement (LoA). Next, for a subsample of 20 forest workers, we produced corrected WM estimates from and compared them to measured WM. Although both methods produced significantly different time-related profiles, they yielded comparable average thermal cardiac reactivity (VOGT: 24.8 bpm °C; KAMP: 24.5 bpm °C), average (LoA: 0.7 ± 11.2 bpm) and average WM estimates (LoA: 0.2 ± 3.4 ml O kgmin for VOGT, and 0.0 ± 5.4 ml O kgmin for KAMP). Both methods are suitable to assess heat stress through and improve WM estimation. We compared two methods for assessing the heart rate thermal component ( ), which is needed to produce a corrected HR profile for estimating work metabolism (WM). Both methods yielded similar estimates that allowed accurate estimations of heat stress and WM at the group level, but they were imprecise at the individual level. AIC: akaike information criterion; bpm: beats per minute; CI: confidence intervals; CV: coefficient of variation in %; CV drift: cardiovascular drift; ΔHR: the heart rate thermal component in bpm; ΔHR: the heart rate thermal component in bpm; ΔΔHR: variation in the heart rate thermal component in bpm; ΔT: variation in core body temperature in °C; HR: heart rate in bpm; HRmax: maximal heart rate in bpm; Icl: cloting insulation in clo; KAMP: Kampmann et al. (2001) method to determe ΔHR; LoA: Limits of Agreement; PMV-PPD: the Predicted Mean Vote and Predicted Percentage Dissatisfied; PHS: Predicted Heat Strain model; RCM: random coefficients model; SD: standard deviation; TC: core body temperature in °C; TCR: thermal cardiac reactivity in bpm °C; τ: rate of change in the heart rate thermal component in bpm min; τ: rate of change in core body temperature in °C min; t: Student's t statistic with level of confidence alpha and n degrees of freedom; TWL: Thermal Work Limit model; : oxygen consumption in ml O kg min; max: maximal oxygen consumption in ml O kg min; VOGT: Vogt et al. (1973) method to determine ΔHR; WBGT: Wet-Bulb Globe Temperature in °C; WM: work metabolism.
心率热成分（ ）会随着体热积累而增加，导致工作代谢（WM）的高估。我们使用两种方法（VOGT 和 KAMP）评估了 35 名森林工人在整个工作班次期间的 ，然后使用协议范围（LoA）比较了工作和休息时的 。接下来，对于 20 名森林工人的子样本，我们从 中生成了校正后的 WM 估计值，并将其与实测 WM 进行了比较。尽管两种方法产生的 时间相关曲线显著不同，但它们产生了可比的平均热心脏反应性（VOGT：24.8 bpm °C；KAMP：24.5 bpm °C）、平均 （LoA：0.7 ± 11.2 bpm）和平均 WM 估计值（LoA：VOGT 为 0.2 ± 3.4 ml O kgmin，KAMP 为 0.0 ± 5.4 ml O kgmin）。这两种方法都适合通过 评估热应激，并改善 WM 估计。我们比较了两种方法来评估心率热成分（ ），这是产生校正 HR 曲线以估计工作代谢（WM）所必需的。两种方法都产生了相似的 估计值，这些估计值允许在组水平上准确估计热应激和 WM，但在个体水平上精度不高。AIC：Akaike 信息准则；bpm：每分钟节拍；CI：置信区间；CV：%的变异系数；CV 漂移：心血管漂移；ΔHR：bpm 中的心率热成分；ΔHR：bpm 中的心率热成分；ΔΔHR：bpm 中心率热成分的变化；ΔT：核心体温的变化°C；HR：bpm 中的心率；HRmax：bpm 中的最大心率；Icl：cloting 绝缘在 clo 中；KAMP：Kampmann 等人（2001 年）方法确定 ΔHR；LoA：协议范围；PMV-PPD：平均预测票数和平均不满意百分比；PHS：预测热应激模型；RCM：随机系数模型；SD：标准偏差；TC：核心体温°C；TCR：bpm °C 中的热心脏反应性；τ：bpm min 中心率热成分的变化率；τ：°C min 中核心体温的变化率；t：置信水平为 alpha 和 n 自由度的学生 t 统计量；TWL：热工作极限模型； ：ml O kg min 中的耗氧量； max：ml O kg min 中的最大耗氧量；VOGT：Vogt 等人（1973 年）方法确定 ΔHR；WBGT：湿球球温度°C；WM：工作代谢。
