## 6 Results
### Signal Detection  
To determine what effect the magnitude of angular jerk has on signal detection, we performed a Pearson's correlation analysis correlating jerk magnitude with a user's hit percentage, miss percentage, and the total number of false alarms per trial. Correlations of the total number of targets per trial are also presented to rule out spurious correlations simply due to the total number of targets. As shown in Table 1, some individual correlations obtained statistical significance, but the majority did not reach set levels of significance. Thus, with so few correlations reaching significance, hypothesis three was not supported.  
Figure 4: Angular jerk magnitude. Levels of angular jerk are shown for both an example AR cued condition as well as a trial when no cues were present. Jerk levels presented for both conditions represent one trial.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{\begin{tabular}{c} **High CV** \\ **Accuracy** \\ \end{tabular} } & \multicolumn{3}{c}{**No Augmentation**} & \multicolumn{3}{c}{**Bounding Box**} & \multicolumn{3}{c}{**Corner Bound**} & \multicolumn{3}{c}{**Outline**} \\ \cline{2-13}  & **Low** & **Medium** & **High** & **Low** & **Medium** & **High** & **Low** & **Medium** & **High** & **Low** & **Medium** & **High** \\  & **(0.12)** & **(0.17)** & **(0.22)** & **(0.12)** & **(0.17)** & **(0.22)** & **(0.12)** & **(0.17)** & **(0.22)** & **(0.12)** & **(0.17)** & **(0.22)** \\ \hline \multirow{2}{*}{\begin{tabular}{c} Hit \\ Percentage \\ \end{tabular} } & \(-0.460\) & \(\mathbf{-0.581}\) & \(0.159\) & \(0.298\) & \(0.140\) & \(0.249\) & \(0.057\) & \(0.193\) & \(0.424\) & \(0.145\) & \(0.244\) & \(0.182\) \\ \hline \multirow{2}{*}{\begin{tabular}{c} Miss \\ Percentage \\ \end{tabular} } & \(0.421\) & \(\mathbf{0.581}\) & \(-0.159\) & \(-0.338\) & \(-0.050\) & \(-0.145\) & \(-0.160\) & \(-0.240\) & \(-0.362\) & \(-0.268\) & \(0.000\) & \(-0.178\) \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} False Alarms \\ \end{tabular} } & \(0.128\) & \(\mathbf{0.559}\) & \(-0.133\) & \(0.005\) & \(0.282\) & \(0.232\) & \(0.411\) & \(-0.343\) & \(-0.189\) & \(\mathbf{0.564}\) & \(-0.251\) & \(0.175\) \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Total Targets \\ \end{tabular} } & \(0.147\) & \(-0.058\) & \(-0.021\) & \(-0.052\) & \(0.229\) & \(-0.312\) & \(0.147\) & \(0.016\) & \(-0.074\) & \(-0.101\) & \(0.342\) & \(0.206\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Correlations for signal detection performance are presented with the high CV accuracy condition presented above and the low CV accuracy condition presented below. Bolded values indicate statistical significance at \(\leq\)0.05.  
Figure 3: Graph of jerk with augmentation type and saliency. Levels of jerk magnitude are shown on both graphs with the left graph (**a**) showing jerk levels for each augmentation type and the right graph (**b**) showing jerk levels in the different saliency conditions. Simulated computer vision accuracy groups (low, high, and combined) are show on of the left graph (**a**) and levels of augmentation saliency (low, medium, and high) are shown in the panels of the graph on the right (**b**). Error bars reflect the standard error of the mean.