| Description |
Heat related illness is especially prominent in working populations that perform routine physical labor in combination with thick and heavy personal protective equipment (PPE) in regions with high ambient temperatures. These factors, when paired with improper dehydration, significantly contribute to the development of heat illness. Heat illness manifests itself in many ways in the human body, such as exercise-associated muscle cramps, heat syncope (dizziness), heat exhaustion, exertional heat stroke, and exertional hyponatremia. The three most prominent contributing factors to this condition are dehydration, over-expending of metabolic energy without proper food intake, and elevated core body temperatures. The goal of this research is to further our understanding of these factors and investigate interactions with easily accessible biometric readings taken in real-time by wearable sensors. Aim 1: Investigate if the Bernard Metabolic equation can be modified to account for altitude. We hypothesized that a statistically significant difference in the metabolic demand of performing an equivalent task exists between working at sea level, 1300 m (4500 ft) above sea level, and 3000 m (10,000 ft) above sea level. Aim 2: Evaluate the predictive capability of the temperature differential between the chest and upper extremities (arms) for full body hydration status. We hypothesized that due to the restriction of blood flow volume to the upper and lower extremities upon dehydration, the nature of heart rate and the temperature differential iv between the arms and chest will change as they lose body mass due to dehydration during steady state exercise. A linear mixed model was utilized to validate our hypothesis and develop a predictive algorithm for full body hydration levels. Aim 3: Develop a regression model to predict core body temperature noninvasively. We hypothesized that heart rate and skin temperature can be used to predict core temperature using a multivariate predictive model. A linear mixed model was again utilized to validate our hypothesis and develop the predictive algorithm for core temperature. This work expands our understanding of the three primary contributors to heat stress. This has implications to develop tools to intervene during the early stages of heat strain before any serious injury or illness occurs. |
