Key result
An integrated exercise thermophysiological model combined with a fuzzy finite state machine can numerically simulate human physiological processes to predict exercise health status.
A novel computational simulation model integrating thermoregulatory and heart rate responses can predict health status during exercise to potentially prevent adverse events.
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May support future exercise monitoring tools; leaves open clinical validation before any practice adoption.
Research of healthy exercise has garnered a keen research for the past few years. It is known that participation in a regular exercise program can help improve various aspects of cardiovascular function and reduce the risk of suffering from illness. But some exercise accidents like dehydration, exertional heatstroke, and even sudden death need to be brought to attention. If these exercise accidents can be analyzed and predicted before they happened, it will be beneficial to alleviate or avoid disease or mortality. To achieve this objective, an exercise health simulation approach is proposed, in which an integrated human thermophysiological model consisting of human thermal regulation model and a nonlinear heart rate regulation model is reported. The human thermoregulatory mechanism as well as the heart rate response mechanism during exercise can be simulated. On the basis of the simulated physiological indicators, a fuzzy finite state machine is constructed to obtain the possible health transition sequence and predict the exercise health status. The experiment results show that our integrated exercise thermophysiological model can numerically simulate the thermal and physiological processes of the human body during exercise and the predicted exercise health transition sequence from finite state machine can be used in healthcare.
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Jia et al. (2017) studied Exercise health status and accidents (dehydration, heatstroke). Integrated human thermophysiological model and fuzzy finite state machine was evaluated on Prediction of exercise health status and transition sequence. An integrated exercise thermophysiological model combined with a fuzzy finite state machine can numerically simulate human physiological processes to predict exercise health status.
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