Development of interactive guidance for cold exposure using a thermoregulatory model.

Area of Science:

• Environmental Science
• Human Physiology
• Protective Clothing Technology

Background:

• The Wind Chill Temperature Index (WCT) has limitations in assessing cold injury risk for specific activities.
• Existing methods lack personalized prediction for frostbite and hypothermia.
• There is a need for advanced decision support for cold weather protection.

Purpose of the Study:

• To introduce the Cold Weather Ensemble Decision Aid (CoWEDA) for selecting optimal cold weather ensembles.
• To enhance the prediction of cold injury risks, including frostbite and hypothermia.
• To provide personalized guidance for cold weather safety and survival.

Main Methods:

• Development of a knowledge-based decision aid (CoWEDA).
• Integration of a validated six-cylinder thermoregulatory model.
• Utilized a clothing properties database and ensemble calculation algorithms.
• Incorporated a user-friendly graphical interface for ensemble selection.

Main Results:

• CoWEDA accurately predicts frostbite and hypothermia risks.
• It ensures selected ensembles provide adequate protection against cold injury.
• Model variant predicts cold water immersion survivability and clothing needs.
• Provides greater individual fidelity in cold injury predictions compared to WCT.

Conclusions:

• CoWEDA significantly enhances cold weather safety guidance beyond WCT.
• It offers personalized risk assessment for frostbite and hypothermia.
• CoWEDA is a valuable tool for selecting protective clothing ensembles for diverse environmental conditions and activities.