Validation of new method for predicting human skin temperatures during cold exposure: The Cold Weather Ensemble Decision Aid (CoWEDA)

Abstract

Abstract Purpose The accuracy of the US Army's Cold Weather Ensemble Decision Aid (CoWEDA) was assessed for the prediction of human skin temperatures while exposed to cold environmental conditions. Methods Data from four laboratory cold exposure studies were combined to examine skin temperature responses based on environment, clothing, and activities. This combined dataset included a total of 23 volunteers exposed to cold conditions between −40 and 0 °C during rest and moderate treadmill walking. Observed measures of mean skin temperature and regional skin temperatures were compared to modeled predictions, where predictive accuracy and precision were evaluated by the bias, mean absolute error (MAE), and root mean square error (RMSE). Results Skin temperature predictions were within an acceptable range of accuracy when compared to observed values (bias, −0.71 ± 2.21 °C; MAE, 1.85 ± 1.75 °C; and RMSE, 2.28 ± 1.54 °C) across all conditions. An acceptable level of predictive accuracy was also observed for finger (bias, −0.98 ± 2.50 °C; MAE, 2.68 ± 2.09 °C; RMSE, 2.68 ± 1.71 °C) and mean skin temperatures (bias, −0.03 ± 1.25 °C; MAE, 1.06 ± 0.65 °C; RMSE, 1.25 ± 0.68 °C). Conclusion The CoWEDA acceptably predicts skin temperatures while at rest and exercise during cold exposure in controlled laboratory conditions.