## 3 Results  
The model's performance metrics were analyzed using different ECG segment lengths and overlap percentages (Table 3). The segment length refers to the duration of each segment, while the overlap percentage indicates the commonness between consecutive segments. A 50% to 90% overlap ensures continuous analysis by capturing transitional data. The decision to use 10 s intervals was supported by previous studies that have demonstrated the effectiveness of this segment length in balancing the granularity of analysis with computational efficiency. Shorter intervals might not capture enough data for accurate assessment, while longer intervals could introduce unnecessary complexity and delays.  
Table 3 details how varying these parameters (segment length and overlap) affected key metrics like the Ac, precision, Se, and F1 score during the assessment of ECG signal quality.  
The ScientISST MOVE dataset provided a rich source of data with 6468 ECG segments of 10 s durations with a 50% overlap. Of these, 3.207 segments (49.58%) were classified as unacceptable, while 3.261 segments (50.42%) were deemed acceptable (Table 4).  
Figure 5 shows the differences in the ECG features between acceptable and unacceptable segments.  
Figure 6 shows examples of ECG signals labeled as acceptable and unacceptable under three different conditions of dynamic firefighter activities: (1) no activity; (2) the minimum difficulty with favorable conditions and no physiological or psychological fatigue; and  
\begin{table}
\begin{tabular}{c c} \hline \hline
**ECG Signal Quality** & **Number of Segments** \\ \hline Unacceptable (0) & 3207 \\ \hline Acceptable (1) & 3261 \\ \hline Total & 6468 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Distribution of ECG signal quality in the ScientISST MOVE dataset, categorized into segments classified as unacceptable (0) and acceptable (1). The classification was based on 10 s interval lengths with a 50% overlap.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**Interval Length (Seconds)**} \\ \cline{3-8}
**Metric** & **Overlap** & **5** & **6** & **7** & **8** & **9  
(3) moderate difficulty with favorable conditions but with physical fatigue. The proportion of acceptable ECG segments within an 8 h shift for each scenario was 32.6% for (1), 37.8% for (2), and 54.7% for (3).  
**Classified 10-Second ECG Signals from Real-Life Conditions of Firefighters**  
Figure 5: Normalized mean values of ECG features for segments categorized as “Quality 0” (unacceptable) and “Quality 1” (acceptable). Each metric is represented by a pair of points connected by a vertical line, with the blue point indicating the average for a quality of 0 and the orange point for a quality of 1. The vertical separation between points of the same metric illustrates the Difif, which represents the absolute difference between the mean values of each metric for “Quality 1” and “Quality 0”; SD0 represents the standard deviation of the metric values for “Quality 0” segments; and SD1 denotes the standard deviation for “Quality 1” segments.  
Figure 6: Classified 10 s ECG signals from firefighters under real-life conditions. The left column shows examples of acceptable signals, while the right column shows unacceptable signals under three different dynamic activity conditions: (1) no activity; (2) the minimum difficulty with favorable conditions and no physiological or psychological fatigue; and (3) moderate difficulty with favorable conditions but with physical fatigue.