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Determining Safe Working Hours of Wearing Medical Disposable Protective Clothing From Physiological Thermal Limits: A Pilot Study

服装 热假人 个人防护装备 医学 法律工程学 工程类 2019年冠状病毒病(COVID-19) 材料科学 复合材料 保温 地理 病理 考古 传染病(医学专业) 疾病 图层(电子)
作者
Jian Li,Xinwen Cui,Qianqian Huang,Jun Li
出处
期刊:AATCC journal of research [SAGE Publishing]
卷期号:11 (3): 171-182
标识
DOI:10.1177/24723444231222564
摘要

Despite the mandatory use of medical disposable protective clothing to protect against infectious hazards, how to determine optimal safe working hours induced by physical fatigue while wearing medical disposable protective clothing remains unknown. Driven by these questions, here we quantify the extent of physical fatigue experienced by medical staff wearing medical disposable protective clothings in isolation wards to identify a safe work duration. Eight healthy males were subjected to light (2.1 km/h) and moderate (4.3 km/h) treadmill exercises while wearing two different ensembles. Four physiological (tympanic temperature T core , mean skin temperature T sk , heart rate, and sweat loss) and two subjective indicators (thermal sensation and humidity sensation) were measured. We then introduced a discrete gray model(1,1) to determine safe working hours. The study indicated that even at lower temperatures, prolonged wearing of medical disposable protective clothing could significantly affect physiological indicators such as T core and T sk ( p < 0.001), with T core being the predominant factor limiting safe working hours. Regarding medical disposable protective clothing-1-light, medical disposable protective clothing-1-moderate, medical disposable protective clothing-2-light, and medical disposable protective clothing-2-moderate intensity activities, the safe working hours were 6.33, 2.83, 2.83, and 2.25 h. This article presented a new approach to determining safe working hours for wearing medical disposable protective clothing from physiological thermal limits with small sample data. However, this is a preliminary study, and further validation of the prediction model through additional experiments is necessary.
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