## 3 Results
### Slate Safety Wearable Sensor  
There was a strong positive correlation between the ICTS and the SS, which was statistically significant (\(p\) (421) = 0.543, \(p\) < 0.001). Thus, hypothesis H1B was met. The one-sample Wilcoxon signed-rank test showed that there was a statistically significant difference between the data from the ICTS and the SS device (\(Z\) = \(-\)11.197, \(p\) < 0.001). This indicates that there is a systematic difference between the devices. Figure 3a showed the outcome of the Bland-Altman plot, which showed a proportional bias and explained where the differences occurred. The red line represents the bias while the green lines represent the upper limit and the lower limit, respectively. The bias was 0.20 \({}^{\circ}\)C, and the RMSE and MAE were evaluated to measure the difference in the CT data from SS and the ICTS. The RMSE value of 0.398 suggests that there is an average difference of 0.398 \({}^{\circ}\)C between the two devices. Similarly, the MAE value of 0.334 indicates that both sensors differ by 0.334 \({}^{\circ}\)C. Equally, linear regression indicated that there is a proportional bias under the distribution of data around the mean difference line (t = \(-\)4.684, \(p\) < 0.001). Figure 3b illustrates the average temperature trends over time for both the SS and ICTS data, considering the variability and dispersion of temperature measurements among participants for the first 20 min. The large variability observed in the participants' SS CT measurement, shown in Figure 3b, prompted the investigation of the impact of individual differences on the CT measurement. The results of the Mann-Whitney U test (Mean_SS \begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**CT Devices**} & \multirow{2}{*}{**Bias**} & \multirow{2}{*}{**Precision (SD)**} & \multicolumn{2}{c}{**95\% Limits of Agreement**} \\ \cline{3-5}  & & & **Lower** & **Upper** \\ \hline Slate Safety & 0.201 & 0.345 & \(-\)0.474 & 0.877 \\ Zephyr & \(-\)0.025 & 0.328 & \(-\)0.668 & 0.618 \\ \hline \hline \end{tabular} SD: standard deviation, CT: core temperature.  
\end{table} 
Table 4: Bias, precision, lower and upper limits value as computed from the Bland–Altman plot. Figure 3: (**a**) A Bland–Altman plot and (**b**) CT data output for the comparison of SS and ICTS (n = 10 participants). CT: U = 7.0, \(p\) = 0.424; Max_SS CT: U = 4.0, \(p\) = 0.138) revealed that participants who never avoided performing exercise in hot condition recorded higher CT (Mean_SS CT Median = 37.58 \({}^{\circ}\)C; Max_SS CT Median = 38.14 \({}^{\circ}\)C) than other participants who sometimes avoid performing exercise in hot condition (Mean_SS CT Median = 37.43 \({}^{\circ}\)C; Max_SS CT Median = 37.78 \({}^{\circ}\)C). However, these differences were found to be statistically insignificant. Next, the Kruskal-Wallis test results indicated that there was no statistically significant effect of exercise intensity on the CT measurements (Mean_SS CT: \(\chi^{2}\)(2) = 0.78, \(p\) < 0.676; Max_SS CT: \(\chi^{2}\)(2) = 3.07, \(p\) < 0.215). However, it is worth noting that participants who engaged in moderate-intensity exercise had the highest CT measurements (Mean_SS CT Median = 37.58 \({}^{\circ}\)C; Max_SS CT Median = 38.14 \({}^{\circ}\)C), followed by those who performed low-intensity exercise (Mean_SS CT Median = 37.55 \({}^{\circ}\)C; Max_SS CT Median = 37.93 \({}^{\circ}\)C), and lastly, participants who engaged in vigorous-intensity exercise (Mean_SS CT Median = 37.43 \({}^{\circ}\)C; Max_SS CT Median = 37.74 \({}^{\circ}\)C). The Kruskal-Wallis test was conducted to examine the relationship between participants' BMI and CT measurements. The results indicated that BMI did not have a statistically significant effect on CT measurement (Mean_SS CT: \(\chi^{2}\)(2) = 1.23, \(p\) < 0.541; Max_SS CT: \(\chi^{2}\)(2) = 0.45, \(p\) < 0.798).