## 4 Other Resources  
### Travel Time Analysis  
To evaluate the effectiveness of different interaction methods for wheelchair users in virtual environments, we conducted three statistical analyses comparing the performance across various conditions: C1 versus C2, C1 versus C3, and C2 versus C3:  
* C1 = interaction with wheelchair and base motors ON;
* C2 = interaction with wheelchair and base motors OFF;
* C3 = interaction with joystick and base motors off.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Gender/Wheelchair Type** & **Quantity** & **Mean Age** \\ \hline F/Manual & 8 & 36.5 \\ F/Motor & 5 & 32.2 \\ M/Manual & 7 & 43.4 \\ M/Motor & 1 & 51 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Demographics of study participants.  
Each analysis aimed to determine the optimal method for enabling natural and efficient movement in immersive virtual reality (VR) settings. The performance metric used in these analyses was the time users took to complete a navigation task within the VR environment.  
In the comparison between C1 and C2, a paired _t_-test revealed a significant difference in user performance. The results showed that users navigated significantly faster with the motors off, as indicated by a t-statistic of 4.001 and a _p_-value of 0.0013. The effect size, measured by Cohen's d, was 1.036, which is considered large, indicating a substantial improvement in performance when the motors were off. The statistical power of this test was 96.1%, suggesting a high likelihood that the observed effect is real and not due to chance. These findings imply that users experience less resistance and greater control without motor assistance.  
The second analysis compared C1 with C3. Here, the paired _t_-test results demonstrated a significant performance difference, with users performing better when using their wheelchairs with base motors on. The t-statistic was \(-3.939\), and the _p_-value was 0.0015, indicating strong statistical significance. The effect size was \(-0.988\), which is also considered large, showing that the use of base motors is far more effective than joystic control. The statistical power for this comparison was 94.4%, reinforcing the reliability of these results. This analysis underscores that while motor assistance might not be optimal, it still offers a better interaction method than joystick control.  
The most pronounced difference was observed in the comparison between C2 and C3. The paired _t_-test yielded a t-statistic of \(-6.046\) and a highly significant _p_-value of \(6.547\times 10^{-6}\). The effect size was a striking \(-1.803\), indicating an extremely large effect. The statistical power for this comparison was 96.8%, indicating that the likelihood of detecting a true effect was virtually certain. These results highlight the superiority of natural interaction methods without motor assistance over joystick control, showing that users can navigate much more efficiently and naturally in the VR environment without relying on a joystick.  
Table 2 summarizes the results of the statistical analysis comparing navigation performance across the three interaction methods. It presents the mean navigation time differences, t-statistics, _p_-values, effect sizes (Cohen's d), and statistical power for each comparison, highlighting the significant differences in user efficiency.