Thermophysiological models and their applications: A review

6 The human body’s heat exchange and its interaction w th the surrounding environment has in the past 7 years been the research focus of a number of discip lines. As a result, a number of human 8 thermoregulation models have been developed since t he first was developed in 1970. The aim of this 9 paper is to conduct a review existing thermophysiol ogical models for the whole body and isolated 10 body segments. The course of the development from s imple to more complex models is shown, and 11 most recognized thermal models such as Fiala, Berke ley Comfort Model, Tanabe, and ThermoSem 12 model are concisely described. Furthermore, possibl e applications of the models in various research 13 disciplines are introduced. In the built environmen t, the developed models are used as part of the 14 methodology for modelling thermal comfort in buildi ngs. 15


M A N U S C R I P T
A C C E P T E D ACCEPTED MANUSCRIPT temperature, core temperature and the rate of the change in skin temperature are the main signals 1 for the active system [13]. The change in brain temperature above the set point results in 2 vasodilation. When vasodilation is not sufficient to lose heat from the body, sweating is activated 3 for the heat losing process. Vasoconstriction is a result of reduction in the skin temperature [38]. 4 However, if the body is exposed to a cold environment and vasoconstriction is not enough to 5 maintain the heat in the body, the body will start to shiver in order to retain heat. Furthermore, the 6 skin blood flow is controlled by the mechanisms of vasodilation and vasoconstriction. [40]) 10 The thermal balance of the body is influenced by local environmental conditions and individual 11 physiological characteristics. The environmental parameters (air temperature, mean radiant 12 temperature, air velocity and relative humidity) and human physiological inputs (metabolic rate, 13 height, weight, fat percentage, blood flow rate, gender, skin surface area etc.) serve as model inputs 14 ( Figure 2). As output, the models are able to predict local skin temperature and the body's core 15 temperature. Thermophysiological models can present the human body as a single segment or the body can be 3 divided into several body parts. Furthermore, the models can be classified as one-node thermal 4 models, two-node thermal models, multi-node thermal models and multi-element thermal models [5]. 5 Figure 3 [6,23] presents different thermophysiological models, from simple to more complex models. 6 One-node models are empirical models that predict thermal responses based on formulas that were 7 derived from experimental conditions. These models simulate a human body as one unit and the 8 thermoregulatory system is not included in the model. Givoni and Goldman developed a one-node 9 model for application in hot environments in 1971. In their model the equations for the metabolic costs 10 of walking, running and carrying load were proposed [5][41]. In two-node models, the human body is divided into two concentric shells of core and skin and the 3 temperature of each shell is considered uniform. Gagge's model is a well-known example of two-node 4 thermal models. The model was developed in 1971 [34] and improved in 1986 (as presented by Foda a two-node model developed by Takada et al. [46] and a two-node model for different body parts 2 developed by Kaynakli and Kilic [47,48]. As it was mentioned above, two-node models represent 3 body as skin, and a central core that represents muscle, subcutaneous tissue and bone. If more detailed 4 temperature distribution is acquired, the body should be divided into more than two nodes that will 5 represent every tissue separately. 6 Multi-node human thermal models are extended and more intricate versions of the two-node model. 7 The first multi-node model was developed by Crosbie [49] and this was the first time that analogue 8 computer was used for the simulation of physiological temperature regulation of the human body [49]. 9 Multi-node models consider an inhomogeneous distribution of temperature and thermoregulatory 10 responses over the body's surface. Vasoconstriction and vasodilatation dispense blood flow to the 11 extremities to control the heat loss from the skin to the environment [3]. Multi-node models with 12 advanced vasomotion models are able to simulate the local skin temperatures of individual body parts 13 ( Figure 4). 14 15 Figure 4. Comparison of the model segmentation, and the two-node models and multi-node models 16 The most influential multi-node model that paved the foundations for many human thermal-modeling 17 studies was developed by Stolwijk The passive part of the Stolwijk model consists of six segments (head, trunk, arms, legs, hands and  3 feet) and each segment is divided into four layers: the core, fat, muscles and skin [10]. The model 4 includes a central blood compartment at a uniform temperature (without distinguishing arteries and 5 veins flow) that is thermally connected to all the other nodes. The effects of counter-current heat 6 exchange in the blood flow and the blood flow characteristics in local tissue are not included in the 7 Stolwijk model.  [58]. 19 According to the classification, the last type of models are multi-element models. Multi-element 20 thermal models in contrast to the multi-node models simulate the human body as several body parts, 21 and no further division is made into nodes. The assumption of uniform node temperatures is not 22 applied and most of the body's different geometric properties are included. All this information must 23 be available thus making these models the most complicated ones [5,6] The Fiala model is a multi-node model that extensively simulates the human body including the 1 predictions of overall and local physiological responses. The model presents an average person with a 2 detailed multi-layered structure of the human body that makes it possible to avoid errors during 3 transient conditions due to the use of lumped data. The body division into layers was made whenever a 4 change of a body tissue properties is present in the human body [7]. The environmental heat exchange 5 was modelled including local heat losses and gains from the body by free and forced convection, solar 6 irradiation, long-wave radiation, evaporation of moisture from the skin and insulation effect of the 7 clothing [7]. 8 The active part that models the thermoregulatory control reactions is included in the Fiala model. 9 When in the state of thermal discomfort, the human body copes with thermal stress by physiological 10 adaptation in order to acclimatize. The body's thermoregulatory control mechanisms are activated 11 when the body is in a state of discomfort. The methodology for modelling essential regulatory 12 responses of the central nervous system is based on a regression analysis of the physiological response 13 of unacclimatised subjects ( Figure 5).  conditions (sever cold, cold, neutral, warm, and hot) and exercise intensities. For each experiment, the 2 passive system was exposed to experimental boundary conditions. Thermoregulatory responses 3 observed in experiments were imposed on the passive system for each moment of exposure. This 4 simulation forms the basis for establishing the line of thermophysiological variables and the measured 5 regulatory responses were subjected to a multi-linear regression to obtain control equations. 6 Furthermore, equations were implemented into the model and re-simulated with experimental data to 7 determine further control equations. The validation of the core and skin temperatures, and 8 thermoregulatory responses are well correlated with the experimental data that cover a wide range of 9 environmental exposure (moderate, hot and cold stress) and activity levels [12]. 10 The UC Berkeley multi-node model is based on the Stolwijk model and the Tanabe model. In 11 developing the model, 16 body segments were used. An advantage of this model is that fine 12 segmentation can be used in environments with local temperature variations. The blood compartments 13 are represented as a separate series of nodes that are responsible for heat transfer between segments 14 and tissue nodes [15]. Thermoregulatory responses of vasomotion, sweating and metabolic heat 15 production are explicitly considered.

Radiation heat flux model is separated into short wave and long wave radiation components
The physiological differences between individuals (height, weight, gender, body fat, hip, neck and 1 abdomen dimensions, and skin color) influence thermal responses. The approach of the Berkeley team 2 is to incorporate the body builder model [14]. The model defines a set of physiological parameters 3 which can be used to study variations in thermal response between different body characteristics [14]. Among the models that were developed based on Stolwijk model are three thermoregulatory models 10 developed by Tanabe and his associates; 65MN, 3DM and Jointed Circulation System (JOS) model 11 [69]. The Tanabe 65-node thermoregulation model, that represents an average man is able to predict 12 the variation of physiological conditions for various parts of the body [11]. The 65th node in the model 13 represents the central blood compartment. As a part of the passive system, heat equations for each 14 layer were calculated and the heat balance between local tissues and central blood pool was simplified. 15 The physiological reactions were formed using control equations that contained sensor signals relating 16 to the head core signal and integrated signals from skin thermoreceptors [11].

M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT
The reason is that the human head is directly exposed to the environment and has to quickly respond to 1 any thermal changes in the surroundings [69]. All the body segments have artery and vein blood pools; 2 core layer and skin layer. Also, superficial veins and arteriovenous anastomoses ( subdivision, the asymmetric boundary conditions could be taken into account [16]. Within the body, 22 heat transfer by conduction and convection was modeled with Pennes' equation (a) [60], and 23 calculation for heat transfer between the body and environment are based on Fiala et al. [16]. 24 In the model, individual characteristics such as height, weight and fat percentage can be taken into 5 account [8]. The model was validated for mild environmental exposures. 6 The main difference between the ThermoSEM model and Fiala's model, is in the active part. By Mathematical thermophysiological models that considered the whole body introduced in earlier 5 sections of this paper became the basis for modelling isolated body parts. Modelling isolated body 6 segments became valuable in medicine, as well as in built environment for assessing the sensitivity of 7 human extremities and other body parts in the different thermal environment (Table 3). 8 A human torso was modelled to investigate how adipose tissue, metabolism heat generation and winter 9 clothes influence the human body's ability to resist hypothermia when exposed to the extreme cold 10 environment [18]. Another research for medical purposes was conducted where thermal analysis 11 using a human finger model was proposed to assess the risk of coronary heart disease. Indirect 12 measurement of vascular health can be the human fingertip temperature variation during the blood 13 flow occlusion. The mathematical model of the heat transfer for the human finger was introduced to 14 show the connection between vascular reactivity and changes in the finger temperature during blood 15 flow occlusion [19]. 16

M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT
Human hands and fingers contain a significantly higher number of arteriovenous anastomoses valves 1 that control vasomotion then the rest of the body parts. The opening of these valves causes the hand 2 temperature to vary in a wide range [76]. In order to achieve an accurate prediction of thermal 3 responses of the extremities, thermophysiological models have to include detailed vascular system. 4 The reason for the less accurate prediction in a whole body model is due to the fact that they do not 5 simulate complex skin blood flow model in the extremities [77]. In order to achieve accurate thermal 6 responses of the extremities, it is necessary to look at the nature of the human brain and heat transfer 7 efficiency connection. When the human body is exposed to a hot or cold environment, heat transfer 8 and the skin blood flow in the circulator system is affected by the central nervous system that has 9 variant reactions during the different exposures. To model isolated body segments it is necessary to 10 have an empirical input of the blood flow crossing the segment that is modelled [77]. 11 A plethora of studies have been done on modelling human extremities [20,21,75,78] as they are the 12 most vulnerable body parts when exposed to the cold environment. Thermal comfort is closely related 13 to the skin temperature of the body extremities. Wang  to maintain thermal comfort to avoid a decrease in proficiency or even injuries of the hand when 23 working in the colder environment. 24 So far thermophysiological models for the whole body and isolated body segments have been 25 described, the next section will focus on the possible application of these models. 26

Application of the thermophysiological model 1
Many different disciplines acknowledged that there is a necessity for predicting human thermal 2 responses in different thermal environments throughout various activities that people are involved in. 3 Considering that, thermophysiological models are a good possibility for different applications in the 4 field of biometeorology, the auto industry, clothing research, medical application, etc. In the following 5 paragraphs, some examples of application will be introduced. 6 7

The Universal Thermal Climate Index (UTCI) 8
Currently, there is a lot of concern on how humans are affected by the climate and weather, and vice 9 versa. Because of the important emerging issues in the field of climate and health, research is focusing 10 on the human thermal comfort assessments that are a subfield of biometeorology. The ground surface 11 covered types at the urban environments affect the thermal conditions [81]. In different fields of 12 human biometeorology, a need has arisen for a universal index that aims to asses physiological 13 responses across a broad spectrum of outdoor thermal conditions (influence of humidity and heat 14 radiation on a human body in a hot environment, as well as wind speed in the cold conditions) [82]. 15 Additionally, local cooling of exposed skin is considered in order to gain more insight in preventing 16 frostbite, pain and numbness. The initiative to work towards the development of a Universal Thermal 17 Climate Index (UTCI) was proposed by Prof. Peter Höppe. In 2005, the COST Action 730 18 strengthened the process by involving more experts from 19 European countries, Australia, New 19 Zealand, Canada and Israel, who had regular meetings. The purpose of these meetings was to work 20 towards merging new knowledge into creating an index that would be international accepted. A 21 potential application of the index is in the field of public weather services (weather reports, warnings) 22 and environmental agencies, public health systems, city authorities, urban planning, tourism and 23 recreation and climate impact research [83][84][85]. The issues addressed in the UTCI development 24 process is shown in Table 4. 25  The model can be applied to evaluate patient's temperature distribution during heart surgery. During 14 cardiac surgery, hypothermia is induced to protect vital organs. Towards the end of the surgery, the 15 core body temperature is restored to the pre-surgery condition. The consequence of the re-warming 16 process is that heat transfer is faster to the trunk and brain then to the extremities. When the by-pass is 17 disconnected, the heat is distributed to the colder extremities causing "afterdrop" in temperature in 18 core body organs. This "afterdrop" can cause post-surgery complications and there is the need to Thermophysiological model was used to predict the physiological state of the spectators exposed to 3 two types of conditions: normal ambient conditions and conditions when spectators are sitting below a 4 semi-transparent stadium roof. The impact of the solar radiation on the thermal state in spectators was 5 analyzed. Results revealed that acute hot stress in spectators can be prevented by different roof design 6 (shading the roof or opaque cover) [91]. 7 The use of thermophysiological models in combination with thermal comfort models to predict 8 physiological responses can identify the reasons for thermal stress and can be used in the analysis of 9 different thermal situations that endangers occupant's health and safety. These predictions can be 10 valuable information when creating optimal design of buildings. Observing the sport stadium example, 11 if the stadium is not adequately designed the spectators in the upper seat can be exposed to the acute 12 hot stress during the hot summer days in warm climates [91]. 13

Assessing the thermal comfort in a car cabin 14
As a part of thermal comfort simulation of the car occupant exposed to the inhomogeneous 15 Thermal satisfaction with the environment is a complex phenomenon influenced by a large number of 1 physical, physiological and non-physical factors, making comfort prediction in the building design 2 phase complicated. Therefore, thermal comfort assessment has been an attractive research topic 3 throughout the years. Since research on physiological responses of the human body started, different 4 models of human thermoregulation have been developed. In this paper, advanced thermoregulation 5 models that were developed in recent years were reviewed. Particular emphasis was given to the 6 existing application of the models. 7 Throug the years, models gradually developed from homogeneous cylinder to two-node models, and 8 further to multi-node models that simulate human body and its regulatory responses in detailed and 9 extensive ways. The developed models are not identical; however certain characteristics are shared. is that often the models are not available. Therefore, the only way to see the simulation results for a 1 specific environment is to observe the figures presented by the authors in published literature. One 2 possibility that could improve the methodology for comparing the accuracy of the models is creating a 3 database that researches could access. The database could include information on simulation accuracy 4 of different models for specific environmental condition and conditions regarding clothing and 5 activity. Table 5 shows the studies, in which the prediction accuracy of different models was 6 compared. 7 8 • Mean and local skin temperature • Mean latent heat loss • Latent heat loss and gain Novieto [55] • Fiala [7,12,13] • Mean skin and rectal temperature The literature review shows the evolution of models in time and how researchers modified the models 10 to match their research needs. The intention is not to criticize or discuss which model is better, but to 11 offer a summary of the main attributes of the models (Table 6). Hopefully, this could be helpful for 12 researches when making a decision which model better suits their needs. 13 • Validated for mild conditions [17] The literature review indicates that even though sophisticated models were developed with 1 advancement in computer evolution, the models are still not ordinarily used when considering daily 2 applications in the built environment. One reason is that the accuracy of the inputs has to be assured in M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT order to incorporate models in the design processes of buildings and daily application of thermal 1 comfort. For example, the study of Veselá et al. [96] accentuated the need for accurate and reliable 2 input data. Another reason is although it is commonly assumed that the physiological state of the 3 human body presents some predictable comfort response, the relation between the simulated outputs of 4 the model and perceived thermal comfort still has to be affirmed. 5

Conclusions 6
The thermophysiological model that provides physiological responses coupled with other non-physical 7 parameters (behavioural and cultural) that influence perceived thermal comfort, is a valuable part of 8 the methodology for modelling thermal sensation. To enable the practical use of a thermophysiological 9 model several topics still need to be explored. 10 To achieve a high percentage of occupant thermal satisfaction in building with reduction of energy use 11 for heating and cooling, occupant's physiological behavior must be taken into account more precisely. 12 Individual differences in human physiology (age, gender, body composition) influence the thermal 13 state of the body and physiological responses, thus creating possible differences in thermal comfort 14 and thermal preferences of occupants. People from different climate areas and different ethnic 15 background may experience thermal comfort and sensation differently in the same environmental 16 conditions. Including physiological and psychological differences can provide more accurate thermal 17 comfort assessment. 18 Till now, human physiological behavior was not integrated into control processes, and including the 19 human being could benefit the process of achieving extended management of energy demand based on 20 the individual occupant. When considering the control of individual comfort in built environment, it is 21 necessary to find critical parameters that predict changes in occupants' comfort. Upper-extremity skin 22 temperature shows a potential as a control indicator (for slightly cool office environments) for 23 individual control of personal conditioning. Previous research introduced modelling isolated human 24 extremities exposed to the extreme environment. The approach of using the simplified 25 thermoregulation model for human extremities exposed to the office environment, that includes human M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT thermoregulatory responses, should be considered for evaluating the skin temperature for human body 1 extremities. The model of human extremities might provide an insight into the relationship between 2 local skin temperature and local thermal comfort, as well as the influence on overall thermal comfort 3 and sensation. Further research should aim to improve the prediction of the local and overall thermal 4 comfort and make a step towards bringing the models closer to the everyday comfort application. 5 6 7 8 Acknowledgments 9 The research is partly funded by the EuroTech Universities Alliance. Further financial support was 10 given by the professional foundation PIT and the educational organization OTIB.