Thermoregulatory model to predict physiological status from ambient environment and heart rate

Abstract

A real-time thermoregulatory model was developed for predicting real-time physiological responses of workers engaged in various tasks for prolonged time. The unique feature of the present model is primarily on metabolic activity inputs derived from minimum non-invasive measures (i.e., heart rate and ambient temperature). In addition, it utilizes individual anthropological characteristics (height, weight, and clothing) as an input to estimate core temperatures (T(c)). The model was validated using data from five laboratory studies (n=63) with varied environments, clothing, and heat acclimation status. Overall, T(c) predictions using this simplified model, corresponded well with measured values (root mean square deviation: 0.05-0.31 degrees C).