Physiological responses of acclimatized construction workers during different work patterns in a hot and humid subtropical area of China

Yasmeen, Shazia; Liu, Hong; Wu, Yuxin; Li, Baizhan

doi:10.1016/j.jobe.2020.101281

Cited by 19 publications

(11 citation statements)

References 43 publications

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“…Generally, occupants' long-term thermal histories in a non-neutral warm/cold climate can make the climate more acceptable (Yasmeen et al, 2020). In our preliminary study in winter conditions Wu et al, 2019b), significant differences in thermal sensation and local skin temperatures were found in two groups with different thermal histories.…”

Section: Introductionmentioning

confidence: 62%

Individual thermal comfort prediction using classification tree model based on physiological parameters and thermal history in winter

Hong

et al. 2021

Build. Simul.

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Individual thermal comfort models based on physiological parameters could improve the efficiency of the personal thermal comfort control system. However, the effect of thermal history has not been fully addressed in these models. In this study, climate chamber experiments were conducted in winter using 32 subjects who have different indoor and outdoor thermal histories. Two kinds of thermal conditions were investigated: the temperature dropping (24-16°C) and severe cold (12°C) conditions. A simplified method using historical air temperature to quantify the thermal history was proposed and used to predict thermal comfort and thermal demand from physical or physiological parameters. Results show the accuracies of individual thermal sensation prediction was low to about 30% by using the PMV index in cold environments of this study. Base on the sensitivity and reliability of physiological responses, five local skin temperatures (at hand, calf, head, arm and thigh) and the heart rate are optimal input parameters for the individual thermal comfort model. With the proposed historical air temperature as an additional input, the general accuracies using classification tree model C5.0 were increased up to 15.5% for thermal comfort prediction and up to 29.8% for thermal demand prediction. Thus, when predicting thermal demands in winter, the factor of thermal history should be considered.

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Section: Introductionmentioning

confidence: 62%

Individual thermal comfort prediction using classification tree model based on physiological parameters and thermal history in winter

Hong

et al. 2021

Build. Simul.

Self Cite

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“…As indicated in Table 1, previous research in this area falls into three categories: (i) research related to the causes of construction disasters , (ii) research related to an analysis of the weather impact on injury and fatal accidents in construction , and (iii) research related to measuring the thermal comfort of construction workers [46][47][48].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Chan et al, 2012 [47] The author developed a heat stress model based on the concept of the wet bulb globe temperature to measure the heat stress of workers. Yasmeen et al, 2020 [48] The author analyzed the environmental and physiological factors affecting the ability and heat stress level in several building and work types in the construction industry.…”

Section: Research Related To the Causes Of Construction Disastersmentioning

confidence: 99%

“…According to previous research, thermal comfort and related levels experienced by construction workers can differ depending on the season. Accident types can also differ depending on the level of thermal comfort [46][47][48]. In this regard, the seasons in Korea are divided into spring (March-May), summer (June-August), autumn (September-November) and winter (December-February) to analyze injury and fatal accidents and weather conditions [49].…”

Section: Classification Of Accident Types and Weather Conditionsmentioning

confidence: 99%

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Exploring Fatalities and Injuries in Construction by Considering Thermal Comfort Using Uncertainty and Relative Importance Analysis

Lee

Jeong

et al. 2021

IJERPH

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Fatal injury and accidents in the construction industry occur under the influence of outdoor weather conditions such as temperature, humidity and wind speed in all four seasons. Previous research in this area has focused on hot and cold weather conditions: hot weather causes heat rash, heat cramps and heat fainting, while cold weather causes fatigue, lumbago, and cold finger sensations. However, other weather conditions are also associated with, and cause, fatal injury and accidents. Accordingly, this study analyzes injury and fatal accidents in the construction industry based on the physiological equivalent temperature (PET) as it pertains to thermal comfort using an uncertainty analysis. Furthermore, using a neural network, relative importance is analyzed considering injury and fatal accidents. This study is conducted in five steps: (i) Establishment of the database, (ii) Classification of accident types and weather conditions, (iii) Calculation of thermal comfort, (iv) Analysis of injury and fatal accidents based on thermal comfort, and (v) Calculation of the relative importance of thermal comfort during injury and fatal accidents. Via the research process, 5317 fatal incidents and 207,802 injuries are analyzed according to 18 accident types in all seasons. It was found that ‘falls’, were the most frequent fatal incident and injury (2804 fatal incidents and 71,017 injuries), with most of these occurring during the autumn season. The probabilities of injury and fatal accidents in the ‘fall’ category are 86.01% and 85.60%, respectively, in the outside comfort ranges. The contribution of this study can provide data for a database on safety management considering weather conditions.

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“…Physiological responses of human body were the basic for thermal perception [1][2][3][4]. Mean skin temperature (MST) is one of the most important physiological parameters reflecting the thermal states of the human body [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Physiological responses of acclimatized construction workers during different work patterns in a hot and humid subtropical area of China

Cited by 19 publications

References 43 publications

Individual thermal comfort prediction using classification tree model based on physiological parameters and thermal history in winter

Individual thermal comfort prediction using classification tree model based on physiological parameters and thermal history in winter

Exploring Fatalities and Injuries in Construction by Considering Thermal Comfort Using Uncertainty and Relative Importance Analysis

Evaluation and modification of the weighting formulas for mean skin temperature of human body in winter conditions

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