## 4 Experimentation and Analysis of Results
### Experimental Results and Analysis
#### 4.3.2 Robustness Experiments  
(1) Evaluation of User Diversity and Cross-User Generalization  
This method evaluates its robustness through a multi-faceted validation framework. First, a dual mechanism assesses:  
Inter-User Variability: The recognition effect of the same gesture executed by different users (Figure 10(a)), where users 1-6 show minimal accuracy differences despite variations in finger width and execution postures. This indicates the method is insensitive to physiological traits like gender, weight, and height. Intra-User Consistency: The recognition stability of different gestures from the same user (Figure 11b), where accuracy fluctuations (within 3.2%) due to gesture amplitude variations do not compromise overall performance. To quantitatively validate generalization to unseen users, a leave-one-user-out cross-validation strategy was adopted. Data from 9 users were used for training, with the remaining 1 user serving as the test set (repeated 10 times). The results (Table 6) show average accuracies of 93.95% (office) and 94.26% (conference room), with most users deviating <\(\pm\)1.0% from the mean. Notable exceptions (e.g., U7's 91.57% in the conference room) likely reflect environmental interference rather than user diversity, demonstrating the model's resilience to outliers. The above experiments confirm the robustness of SE-WiGR between inter-user physiological differences and intra-user gesture variations, making it suitable for real-world deployments with different user groups. (2) Impact of speed diversity  
Speed is a crucial perceptual dimension when evaluating the impact of WiFi-based devices on gesture recognition, as the same gesture displays unique speed characteristics at various execution speeds. To comprehensively verify the stability and reliability of the gesture recognition system under different speed conditions, in this study, the gesture execution duration of 4 s, as defined in the training dataset, is adopted as the baseline. To \begin{table}
\begin{tabular}{c c c c c} \hline
**Test User** & **Office Accuracy (\%)** & **Deviation from Mean** & **Conference Room Accuracy (\%)** & **Deviation from Mean** \\ \hline U1 & 93.43\% & \(-\)0.52\% & 94.13\% & \(-\)0.13\% \\ U2 & 92.76\% & \(-\)1.19\% & 94.67\% & +0.41\% \\ U3 & 93.85\% & \(-\)0.10\% & 94.32\% & +0.06\% \\ U4 & 93.79\% & \(-\)0.16\% & 93.89\% & \(-\)0.37\% \\ U5 & 94.57\% & \(+\)0.62\% & 94.98\% & +0.72\% \\ U6 & 94.28\% & \(+\)0.33\% & 93.64\% & \(-\)0.62\% \\ U7 & 93.56\% & \(-\)0.39\% & 91.57\% & \(-\)2.69\% \\ U8 & 93.44\% & \(-\)0.51\% & 95.80\% & +1.54\% \\ U9 & 94.88\% & \(+\)0.93\% & 94.27\% & +0.01\% \\ U10 & 94.98\% & \(+\)1.03\% & 95.32\% & +1.06\% \\ Average & **93.95\%** & — & **94.26\%** & — \\ \hline \end{tabular}
\end{table} 
Table 6: Cross-user generalization performance. Figure 11: Recognition results of different users in two environments. (**a**) Recognition results of the same action by different users. (**b**) Recognition results of different actions of the same user. assess the system's robustness across temporal variations, a set of controlled experiments is conducted at three distinct gesture speeds: rapid (2 s), standard (4 s), and slow (6 s). The results of these experiments are shown in Table 7.  
As shown in Table 7, gesture speed significantly affects recognition accuracy. The average accuracy is 89.66% for fast gestures, 93.95% for normal-speed gestures, and 92.80% for slow gestures. Normal-speed gestures yield the highest accuracy, with Up and Down gestures reaching 94.31% and 94.65%, respectively. In contrast, fast-speed Enlarge and Narrow gestures have the lowest accuracy at 88.57% and 87.72%, while the Down gesture performs best at this speed (91.75%). For slow gestures, Left and Right gestures achieve the highest accuracy (93.37% and 93.46%, respectively), whereas Enlarge accuracy drops to 91.36%. At normal speeds, gestures exhibit stable and easily detectable signal variations, resulting in higher accuracy.