Temperature profiles within the human body are highly dependent on the geometry and inhomogeneity of the body. Physical parameters such as density and heat conductivity of the various tissues and variables such as blood flow and metabolic heat production of different organs are spatially distributed and thereby influence the temperature profiles within the human body. Actual physiological knowledge allows one to take into account up to 54 different spatially distributed values for each parameter. An adequate representation of the anatomy of the body requires a spatial three-dimensional grid of at least 0.5-1.0 cm. This is achieved by photogrammetric treatment of three-dimensional anatomic models of the human body. As a first essential result, the simulation system has produced a realistic picture of the topography of temperatures under neutral conditions. Compatibility of reality and simulation was achieved solely on the basis of physical considerations and physiological data base. Therefore the simulation is suited to the extrapolation of temperature profiles that cannot be obtained experimentally.
In this study we use a three-dimensional model of the human thermal system, the spatial grid of which is 0.5 ... 1.0 cm. The model is based on well-known physical heat-transfer equations, and all parameters of the passive system have definite physical values. According to the number of substantially different areas and organs, 54 spatially different values are attributed to each physical parameter. Compatibility of simulation and experiment was achieved solely on the basis of physical considerations and physiological basic data. The equations were solved using a modification of the alternating direction implicit method. On the basis of this complex description of the passive system close to reality, various lumped and distributed parameter control equations were tested for control of metabolic heat production, blood flow and sweat production. The simplest control equations delivering results on closed-loop control compatible with experimental evidence were determined. It was concluded that it is essential to take into account the spatial distribution of heat production, blood flow and sweat production, and that at least for control of shivering, distributed controller gains different from the pattern of distribution of muscle tissue are required. For sweat production this is not so obvious, so that for simulation of sweating control after homogeneous heat load a lumped parameter control may be justified. Based on these conclusions three-dimensional temperature profiles for cold and heat load and the dynamics for changes of the environmental conditions were computed. In view of the exact simulation of the passive system and the compatibility with experimentally attainable variables there is good evidence that those values extrapolated by the simulation are adequately determined. The model may be used both for further analysis of the real thermoregulatory mechanisms and for special applications in environmental and clinical health care.
A one-dimensional model of human thermo-regulation is used to solve a variety of basic problems in determining an adequate structure of the controller for metabolic heat production, skin blood flow and sweat production. Assuming one integrated central and one integrated peripheral afferent signal the controller parameters are evaluated by analysis of the control performance. Based on a validation by experimental results this allows the determination of a first optimized set of values for controller gains and weight of skin temperature feedback. Furthermore we analyse the effect of inhomogeneous distribution of heat production and blood flow, the influence of body fat content, of controller gains, of weight of skin temperature feedback and of depth of peripheral receptors on the dynamic performance. Increase of peripheral blood flow in particular evokes essentially both an increase of energy requirement in the cold and a quicker system response. Differing rates of increase of metabolic heat production are the consequence of differing body fat content. The weight of skin temperature feedback can be limited to 5...20%, because values outside this range evoke dynamic responses incompatible with the experiments. The actual value can only be determined if there is a correct assumption for the depth of the skin receptors. The use of measured superficial skin temperatures brings about an underestimation of the peripheral afferent signal. Of the controller gains it is primarily the gain of the metabolic controller which affects the dynamic response of the system. The experimental fact of a delayed onset of sweat production after a transition from cold to heat is the consequence of a high gain of the vasomotor system.
The structure of the central temperature controller in rabbits has been analysed. On the one hand, experiments were carried out to obtain the necessary data for system analysis; on the other hand, a mathematical model of the passive system was developed which describes the thermal characteristics of the body in accordance with the experimental results. In applying the model, different controller equations for the effector mechanisms involved were tested to fit the experimental data best. They are compared with already existing models of metabolic control. In addition, mechanisms of the effector coordination are discussed. It is shown that the three effectors make use of a similar controller structure that feeds core temperature as well as skin temperature back into the controller. The system is insensitive to variations of the controller gains, whereas a slight change in the controller reference temperature causes significant changes of the controlled core temperature. Furthermore it is shown that any mutual effector blockings are dispensible.
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