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Modeling the sweat regulation mechanism is important for reliable simulation of the human thermoregulatory processes. The complexity of the mechanism makes it very difficult to model using traditional techniques. An engineering or systems overview of the human thermoregulatory system is reported. An extensive review of previous attempts to model the human sweat rate forms an important part of this paper. In addition, this study investigates the applicability of neural networks to the problem of modeling the complex nonlinearities of the sweat regulatory mechanism. It is believed that neural networks provide better generalization capabilities for all the cited dependencies resulting in better sweat prediction models. The network is thus in a position to generalize based on the different operating conditions and provide more reliable outputs over an entire range of environments and metabolic profiles.

A unique exercise facility has been developed and used to simulate orbital extravehicular activity (EVA). The device incorporates an arm ergometer into a mechanism which places the subject in the zero-g neutral body posture. The intent of this configuration is to elicit muscular, cardiovascular, respiratory, and thermoregulatory responses similar to those observed during orbital EVA. Experiments done with this facility will help characterize the astronaut's dynamic heat balance during EVA and will eventually lead to the development of an automated thermal control system which would more effectively maintain thermal comfort.

Automatic control of the liquid cooling garment (LCG) worn by astronauts during extravehicular activity (EVA) would more efficiently regulate astronaut thermal comfort and improve astronaut productivity. An experiment was conducted in which subjects performed exercise profiles on a unique, supine upper body ergometer to elicit physiological and thermal responses similar to those achieved during zero-g EVAs. Results were analyzed to quantify metabolic rate, various body temperatures, and other heat balance parameters. Such data may lead to development of a microprocessor-based system to automatically maintain astronaut heat balance during extended EVAs.