Validation and enhancement of two predictive models evaluating physiological strain during physical work while...

The prediction of physiological strain is essential for the safety of personnel in high-risk environments especially when wearing personal protective equipment (PPE). This study aimed to develop a usability-enhanced variant of the Heat Strain Decision Aid (HSDA), named HSDA-FL (FAME Lab), by implementing automatic workload estimations, alternative environmental inputs, and a revised initialization delay logic. The second aim was to evaluate whether these modifications preserved the original model's validity. The third aim was to evaluate the performance of HSDA, HSDA-FL, and the PHS-FL models while wearing chemical, biological, radiological, and nuclear (CBRN) PPE. Eleven acclimatized participants completed a 40-min simulated CBRN reconnaissance scenario involving walking and inspection tasks. The HSDA-FL was tested with both the original and the revised delay logic, demonstrated significantly lower residual errors than the original HSDA (p<0.001), with the revised delay logic variant achieving the highest accuracy (MAE=0.151°C, RMSE=0.191°C, bias=0.011°C). In contrast, the PHS-FL performed significantly worse than all HSDA-based models (p<0.001). These findings confirm that HSDA-FL maintains and slightly exceeds the predictive validity of the original HSDA while improving usability, whereas PHS-FL was not deemed sufficiently reliable for use with CBRN clothing.