Development of interactive guidance for cold exposure using a thermoregulatory model

• Published in: International Journal of Circumpolar Health
• Main Authors: Xiaojiang Xu, Timothy Rioux, Karl Friedl, Julio Gonzalez, John Castellani
• Format: Article in Journal/Newspaper
• Language: English
• Published: Taylor & Francis Group 2023
• Subjects: Cold stress; cold injury; frostbite; cold weather ensemble; manikin; decision aid; Arctic medicine. Tropical medicine; RC955-962; Arctic; Circumpolar Health; International Journal of Circumpolar Health
• Online Access: https://doi.org/10.1080/22423982.2023.2190485; https://doaj.org/article/10f25ced35fe47138e7383ca5c2a48ef

ABSTRACTFor decades, the Wind Chill Temperature Index (WCT) and its various iterations have been used to assess the risk of frostbite on unclothed body parts. This paper presents an innovative knowledge-based Cold Weather Ensemble Decision Aid (CoWEDA) that can be used to guide the selection of the most appropriate cold weather ensemble(s) relative to anticipated mission physical activities and environmental conditions. CoWEDA consists of a validated six-cylinder thermoregulatory model, a database of clothing properties, algorithms for calculating the whole ensemble properties from individual garments and a graphical user interface. The user-friendly CoWEDA allows users to select from an inventory of clothing items to build an ensemble suitable for their needs. CoWEDA predicts the risks of both frostbite and hypothermia and ensures that a selected clothing ensemble will provide adequate protection to prevent cold injury. CoWEDA predictions provide not only estimates of frostbite risk similar to WCT tables but also hypothermia times and clothing required to prevent cold injuries. In addition, a CoWEDA model variant can predict survivability and clothing requirements during cold water immersion. Thus, CoWEDA represents a significant enhancement of the WCT-based guidance for cold weather safety and survival by providing greater individual fidelity in cold injury predictions.