## 3 Results
### Work Stability and Movement Pattern
#### 3.2.2 Movement Pattern Analysis  
The ankle-mounted IMU sensors provided detailed information on lower limb movement patterns during task execution. Analysis of these movement patterns focused on step cycle characteristics, movement smoothness, and temporal consistency across repeated work cycles for each task type. Figure 7 presents the absolute acceleration profiles over multiple work cycles for representative participants in each task condition. The \(x\)-axis represents time in seconds (0-6 s), corresponding to consecutive work cycles, with each cycle representing a complete task sequence. The \(y\)-axis displays acceleration (m/s\({}^{2}\)), calculated as the vector sum of triaxial acceleration measured from ankle-mounted IMU sensors. The purple lines  
Figure 6: Postural Stability Comparison (Sway Area). \begin{table}
\begin{tabular}{c l c c c c} \hline \hline
**Metric** & **Task** & **Without Exoskeleton** & **With Exoskeleton** & **Improvements (\%)** & \(p\)**-Value** \\ \hline \multirow{8}{*}{Sway Area (cm\({}^{2}\))} & CT-Low & 15.4 \(\pm\) 2.3 & 11.2 \(\pm\) 2.8 & 27.3 & \textless{}0.001 \\  & CT-High & 19.8 \(\pm\) 3.1 & 13.2 \(\pm\) 2.0 & 33.3 & \textless{}0.001 \\  & MT-Low & 12.7 \(\pm\) 1.9 & 8.7 \(\pm\) 1.4 & 31.5 & \textless{}0.001 \\  & MT-High & 17.5 \(\pm\) 2.8 & 11.3 \(\pm\) 1.7 & 35.4 & \textless{}0.001 \\  & ST-Low & 14.3 \(\pm\) 2.2 & 10.8 \(\pm\) 1.6 & 24.8 & \textless{}0.001 \\  & ST-High & 18.2 \(\pm\) 2.9 & 12.5 \(\pm\) 1.9 & 31.3 & \textless{}0.001 \\ \hline \multirow{8}{*}{Mean Sway Velocity (cm/s)} & CT-Low & 5.2 \(\pm\) 0.8 & 3.9 \(\pm\) 0.6 & 25.0 & \textless{}0.001 \\  & CT-High & 6.8 \(\pm\) 1.1 & 4.7 \(\pm\) 0.7 & 30.9 & \textless{}0.001 \\ \cline{1-1}  & MT-Low & 4.5 \(\pm\) 0.7 & 3.6 \(\pm\) 0.5 & 20.0 & \textless{}0.001 \\ \cline{1-1}  & MT-High & 6.3 \(\pm\) 1.0 & 4.3 \(\pm\) 0.6 & 31.7 & \textless{}0.001 \\ \cline{1-1}  & ST-Low & 4.8 \(\pm\) 0.7 & 3.7 \(\pm\) 0.6 & 22.9 & \textless{}0.001 \\ \cline{1-1}  & ST-High & 5.9 \(\pm\) 0.9 & 4.2 \(\pm\) 0.6 & 28.8 & \textless{}0.001 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Postural stability metrics with and without exoskeleton. represent movement with the exoskeleton, while the green lines indicate movement without the exoskeleton. Across all tasks, exoskeleton use resulted in lower acceleration peaks and smoother movement patterns compared to working without the device. The cyclical patterns visible in each graph correspond to the repetitive nature of construction tasks, with peaks occurring during dynamic movement phases and valleys during transitions. Notably, the acceleration peaks observed in the green lines (without exoskeleton) are significantly higher than those in the purple lines, indicating that exoskeleton use helps mitigate abrupt movements and enables more controlled motion. This visualization emphasizes absolute acceleration values rather than relative patterns, providing a direct comparison of movement intensity across conditions. The results suggest that exoskeleton use enhances movement consistency and stability while reducing the overall impact forces experienced during construction tasks. A key finding from the movement pattern analysis was the increased temporal consistency when wearing the exoskeleton. As shown in Table 4, the coefficient of variation (CV) for work cycle duration decreased substantially across all tasks when using the exoskeleton, indicating more consistent and predictable movement patterns. For the sack carrying task (CT), the cycle duration CV decreased from 12.8% to 8.5% in low-intensity conditions and from 15.3% to 9.2% in high-intensity conditions when wearing the exoskeleton, representing improvements of 33.6% and 39.9%, respectively. The upper graph in Figure 7 clearly shows that the peaks in acceleration (particularly at the \"High\" points) were attenuated with exoskeleton use, suggesting improved control during the carrying phase of the task.