Bioheat modeling of elderly and young for prediction of physiological and thermal responses in heat-stressful conditions

How outdoor horticultural activities affect elderly adults' thermal, physiological and psychological responses: a field study

We recruited 162 healthy elderly adults to determine the thermal, physiological, and psychological effects of horticultural activities (flower arranging, transplanting, and rubble masonry) in outdoor open spaces. We linked these to local climate conditions, physiology, and comfort through a questionnaire survey. The results showed that: (1) the neutral physiological equivalent temperature (NPET) before the horticultural activities were 22.18 ℃ for flower arranging, 23.67 ℃ for transplanting, and 20.78 ℃ for rubble masonry, while the NPET decreased to 18.53 ℃, 20.73 ℃ and 18.04 ℃ (respectively) after activities. (2) The heart rate and blood oxygen saturation changed significantly (p < 0.05) only after rubble masonry. (3) The average positive affect (PA) scores increased after flower arranging by 4.83, transplanting by 3.30, and rubble masonry by 4.00. (4) After activities, the thermal sensation vote was mainly influenced by globe temperature (41.36%), air temperature (33.47%), and wind speed (25.17%). Thermal comfort vote could be promoted because of 37.35% of an increasing positive and 21.20% of decreasing negative emotion.

A thermoregulation model based on the physical and physiological characteristics of Chinese elderly

Given the increasing aging population and rising living standards in China, developing an accurate and straightforward thermoregulation model for the elderly has become increasingly essential. To address this need, an existing one-segment four-node thermoregulation model for the young was selected as the base model. This study developed the base model considering age-related physical and physiological changes to predict mean skin temperatures of the elderly. Measured data for model optimization were collected from 24 representative healthy Chinese elderly individuals (average age: 67 years). The subjects underwent temperature step changes between neutral and warm conditions with a temperature range of 25-34 °C. The model's demographic representation was first validated by comparing the subjects' physical characteristics with Chinese census data. Secondly, sensitivity analysis was performed to investigate the influences of passive system parameters on skin and core temperatures, and adjustments were implemented using measurement or literature data specific to the Chinese elderly. Thirdly, the active system was modified by resetting the body temperature set points. The active parameters to control thermoregulation activities were further optimized using the TPE (Tree-structured Parzen Estimator) hyperparameter tuning method. The model's accuracy was further verified using independent experimental data for a temperature range of 18-34 °C for Chinese elderly. By comprehensively considering age-induced thermal response changes, the proposed model has potential applications in designing and optimizing thermal management systems in buildings, as well as informing energy-efficient strategies tailored to the specific needs of the Chinese elderly population.

An individualized and multi-segmental bioheat model for predicting local conditions of the human body under various thermal environments

Thermoregulatory bioheat models have attracted the attention of researchers due to their conformity with the basis of human thermal perception. For this reason, various models have been presented, such as simplified thermoregulatory bioheat (STB), individualized thermoregulatory bioheat (ITB), and multi-segmental thermoregulatory bioheat (MSTB). In the present study and based upon previous models, an individual multi-segment thermoregulatory bioheat (IMTB) model has been introduced. In this model, the body is subdivided into 17 segments and 3 layers, with the blood circulatory system consisting of arteries, veins, and superficial veins. Also, IMTB can evaluate the individual parameters effects (such as height, weight, gender, and age) on physiological parameters and active/passive systems. Finally, this new model was evaluated in human thermal response predictions over a wide range of transient and steady-state environmental conditions (5.0< Tair(°C) <50.0, 31.0 < RH (%)<70.0) and various individual characteristics (male and female, 20 < age (years) < 69, 50 Collapse

Key Words

• Blood circulatory system
• Individual characteristics
• Local skin temperature
• Multi-segment
• Thermoregulatory bioheat model
• Transient thermal environment

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Affiliation(s)

Mahdi Afzalian Mechanical Engineering, University of Birjand, Iran.
Seyed Alireza Zolfaghari Mechanical Engineering, University of Birjand, Iran.

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Prediction of human thermal comfort preference based on supervised learning

Human thermal comfort is relevant to human life comfort and plays a pivotal role in occupational health and thermal safety. To ensure that intelligent temperature-controlled equipment can deliver a sense of cosiness to people while improving its energy efficiency, we designed a smart decision-making system that sets the thermal comfort adjustment preference as a label, reflecting both the human body's thermal feeling and its acceptance of the thermal environment. By training a series of supervised learning models underpinned by environmental and human features, the most appropriate adjustment mode in the current environment was predicted. To bring this design into reality, we tried six supervised learning models, and then, by comparison and evaluation, we identified that the Deep Forest's performance was the best. The model takes into account objective environmental factors and human body parameters. In this way, it can achieve high accuracy in application and good simulation and prediction results. The results can provide feasible references for feature selection and model selection in further research with the aim of testing thermal comfort adjustment preference. The model can provide recommendations for the thermal comfort preference in a specific place at a particular time, as well as guidance on human thermal comfort preference and thermal safety precautions in specific occupational groups.

Analysis of body heat tolerance of workers in a simulated warm environment based on linear mixed model

Workers' heat tolerance plays a crucial role in maintaining their health and performance in hot environments. This study aimed to empirically analyze the body heat tolerance of workers under a simulated warm environment. Twenty healthy male workers from the typical light metal industry (age: 23.15±2.45 years) were participated in the experimental study. Workers were exposed to two thermal environments (Ta = 22°C, RH = 35%, and Ta = 35°C, RH = 35%) in a simulated moderate workload in a climate-controlled room. The maximal aerobic capacity (VO2 max) and body fat mass of workers were determined. The heat tolerance indicators were determined based on heart rate (HR) and ear temperature (ET) before and after each experiment. A linear mixed model was employed to analyze body heat tolerance indicators using the SPSS statistical package. All physiological responses significantly increased in the warm air condition compared to the thermoneutral condition. The HR and ET increased by an average of 14 bpm and 0.75°C, respectively (p<0.05). The mixed model could accurately predict heat tolerance indicators (r = 0.95 and r = 0.97) so that the VO2 max and body fat mass were identified as the main individual influential factors. The VO2 max showed significant correlation with urinary specific gravity (r = -0.55, p<0.05), HR (r = -0.59, p<0.05), and ET (r = -0.57, p<0.05) in warm environment. The model confirmed that physical fitness is critical in increasing heat tolerance in warm environments. It can be a helpful screening tool for properly selecting workers in occupational medical examinations for working in warm air conditions. It is proposed that workers' regular exercise and lifestyle modifications can strengthen their heat tolerance.

Effects of Environmental and Socioeconomic Inequalities on Health Outcomes: A Multi-Region Time-Series Study

The gradual increase in temperatures and changes in relative humidity, added to the aging and socioeconomic conditions of the population, may represent problems for public health, given that future projections predict even more noticeable changes in the climate and the age pyramid, which require analyses at an appropriate spatial scale. To our knowledge, an analysis of the synergic effects of several climatic and socioeconomic conditions on hospital admissions and deaths by cardiorespiratory and mental disorders has not yet been performed in Brazil. Statistical analyses were performed using public time series (1996-2015) of daily health and meteorological data from 16 metropolitan regions (in a subtropical climate zone in South America). Health data were stratified into six groups according to gender and age ranges (40-59; 60-79; and ≥80 years old) for each region. For the regression analysis, two distributions (Poisson and binomial negative) were tested with and without zero adjustments for the complete series and percentiles. Finally, the relative risks were calculated, and the effects based on exposure-response curves were evaluated and compared among regions. The negative binomial distribution fit the data best. High temperatures and low relative humidity were the most relevant risk factors for hospitalizations for cardiovascular diseases (lag = 0), while minimum temperatures were important for respiratory diseases (lag = 2 or 3 days). Temperature extremes, both high and low, were the most important risk factors for mental illnesses at lag 0. Groups with people over 60 years old presented higher risks for cardiovascular and respiratory diseases, while this was observed for the adult group (40-59 years old) in relation to mental disorders. In general, no major differences were found in the results between men and women. However, regions with higher urbanization levels presented risks, mainly for respiratory diseases, while the same was observed for cardiovascular diseases for regions with lower levels of urbanization. The Municipal Human Development Index is an important factor for the occurrence of diseases and deaths for all regions, depending on the evaluated group, representing high risks for health outcomes (the value for hospitalization for cardiovascular diseases was 1.6713 for the female adult group in the metropolitan region Palmas, and the value for hospitalization for respiratory diseases was 1.7274 for the female adult group in the metropolitan region Campo Mourão). In general, less developed regions have less access to adequate health care and better living conditions.

A Multi-Segmented Human Bioheat Model for Asymmetric High Temperature Environments

In workplaces such as steel, power grids, and construction, firefighters and other workers often encounter non-uniform high-temperature environments, which significantly increase the risk of local heat stress and local heat discomfort for the workers. In this paper, a multi-segment human bioheat model is developed to predict the human thermal response in asymmetric high-temperature environments by considering the sensitivity of the modeling to angular changes in skin temperature and the effects of high temperatures on human thermoregulatory and physiological responses simultaneously. The extended model for asymmetric high-temperature environments is validated with the current model results and experimental data. The result shows that the extended model predicts the human skin temperature more accurately. Under non-uniform high-temperature conditions, the local skin temperature predictions are highly consistent with the experimental data, with a maximum difference of 2 °C. In summary, the proposed model can accurately predict the temperature of the human core and skin layers. It has the potential to estimate human physiological and thermoregulatory responses under uniform and non-uniform high-temperature environments, providing technical support for local heat stress and local thermal discomfort protection.

Indoor Air Quality in Elderly Centers: Pollutants Emission and Health Effects

The world population is ageing, in particular in the developed world, with a significant increase in the percentage of people above 60 years old. They represent a segment of the population that is more vulnerable to adverse environmental conditions. Among them, indoor air quality is one of the most relevant, as elders spend comparatively more time indoors than younger generations. Furthermore, the recent COVID-19 pandemic contributed immensely to raising awareness of the importance of breathing air quality for human health and of the fact that indoor air is a vector for airborne infections and poisoning. Hence, this work reviews the state of the art regarding indoor air quality in elderly centers, considering the type of pollutants involved, their emission sources, and their health effects. Moreover, the influence of ventilation on air quality is also addressed. Notwithstanding the potential health problems with the corresponding costs and morbidity effects, only a few studies have considered explicitly indoor air quality and its impacts on elderly health. More studies are, therefore, necessary to objectively identify what are the impacts on the health of elderly people due to the quality of indoor air and how it can be improved, either by reducing the pollutants emission sources or by more adequate ventilation and thermal comfort strategies.