Style figures in visual-hand chapter

4-manipulation/visual-hand/3-0-results.tex

@@ -4,7 +4,7 @@
 Results of each trial metrics were analyzed with an \ANOVA on a \LMM model, with the order of the two manipulation tasks and the six visual hand renderings (\factor{Order}), the visual hand renderings (\factor{Hand}), the target volume position (\factor{Target}), and their interactions as fixed effects and the \factor{Participant} as random intercept.
 For every \LMM, residuals were tested with a Q-Q plot to confirm normality.
 On statistically significant effects, estimated marginal means of the \LMM were compared pairwise using Tukey's \HSD test.
-Only significant results were reported.
+Only significant results are reported.
 
 Because \response{Completion Time}, \response{Contacts}, and \response{Time per Contact} measure results were Gamma distributed, they were first transformed with a log to approximate a normal distribution.
 Their analysis results are reported anti-logged, corresponding to geometric means of the measures.

4-manipulation/visual-hand/3-1-push.tex

@@ -3,9 +3,9 @@
 
 \paragraph{Completion Time}
 
-On the time to complete a trial, there were two statistically significant effects: %
-\factor{Hand} (\anova{5}{2868}{24.8}, \pinf{0.001}, see \figref{results/Push-ContactsCount-Hand-Overall-Means}) %
-and \factor{Target} (\anova{7}{2868}{5.9}, \pinf{0.001}).
+On the time to complete a trial, there were two statistically significant effects:
+\factor{Hand} (\anova{5}{3385}{5.5}, \pinf{0.001}, see \figref{results/Push-CompletionTime})
+and \factor{Target} (\anova{7}{3385}{22.9}, \pinf{0.001}).
 \level{Skeleton} was the fastest, more than \level{None} (\percent{+18}, \p{0.005}), \level{Occlusion} (\percent{+26}, \pinf{0.001}), \level{Tips} (\percent{+22}, \pinf{0.001}), and \level{Contour} (\percent{+20}, \p{0.001}).
 
 Three groups of targets volumes were identified:
@@ -15,11 +15,11 @@ and (3) back \level{B} and \level{LB} targets were the slowest (\p{0.04}).
 
 \paragraph{Contacts}
 
-On the number of contacts, there were two statistically significant effects: %
-\factor{Hand} (\anova{5}{2868}{6.7}, \pinf{0.001}, see \figref{results/Push-ContactsCount-Hand-Overall-Means}) %
-and \factor{Target} (\anova{7}{2868}{27.8}, \pinf{0.001}).
+On the number of contacts, there were two statistically significant effects:
+\factor{Hand} (\anova{5}{3385}{6.2}, \pinf{0.001}, see \figref{results/Push-ContactsCount})
+and \factor{Target} (\anova{7}{3385}{25.6}, \pinf{0.001}).
 
-Less contacts were made with \level{Skeleton} than with \level{None} (\percent{-23}, \pinf{0.001}), \level{Occlusion} (\percent{-26}, \pinf{0.001}), \level{Tips} (\percent{-18}, \p{0.004}), and \level{Contour} (\percent{-15}, \p{0.02});
+Fewer contacts were made with \level{Skeleton} than with \level{None} (\percent{-23}, \pinf{0.001}), \level{Occlusion} (\percent{-26}, \pinf{0.001}), \level{Tips} (\percent{-18}, \p{0.004}), and \level{Contour} (\percent{-15}, \p{0.02});
 and less with \level{Mesh} than with \level{Occlusion} (\percent{-14}, \p{0.04}).
 This indicates how effective a visual hand rendering is: a lower result indicates a smoother ability to push and rotate properly the cube into the target, as one would probably do with a real cube.
 
@@ -27,9 +27,9 @@ Targets on the left (\level{L}, \level{LF}) and the right (\level{R}) were easie
 
 \paragraph{Time per Contact}
 
-On the mean time spent on each contact, there were two statistically significant effects: %
-\factor{Hand} (\anova{5}{2868}{8.4}, \pinf{0.001}, see \figref{results/Push-MeanContactTime-Hand-Overall-Means}) %
-and \factor{Target} (\anova{7}{2868}{19.4}, \pinf{0.001}).
+On the mean time spent on each contact, there were two statistically significant effects:
+\factor{Hand} (\anova{5}{3385}{7.7}, \pinf{0.001}, see \figref{results/Push-MeanContactTime})
+and \factor{Target} (\anova{7}{3385}{17.9}, \pinf{0.001}).
 
 It was shorter with \level{None} than with \level{Skeleton} (\percent{-10}, \pinf{0.001}) and \level{Mesh} (\percent{-8}, \p{0.03});
 and shorter with \level{Occlusion} than with \level{Tips} (\percent{-10}, \p{0.002}), \level{Contour} (\percent{-10}, \p{0.001}), \level{Skeleton} (\percent{-14}, \p{0.001}), and \level{Mesh} (\percent{-12}, \p{0.03}).
@@ -46,7 +46,7 @@ Targets on the left (\level{L}, \level{LF}) and the right (\level{R}) sides had
   \item Number of contacts with the cube.
   \item Time spent on each contact.
   ]
-  \subfig[0.32]{results/Push-CompletionTime-Hand-Overall-Means}
-  \subfig[0.32]{results/Push-ContactsCount-Hand-Overall-Means}
-  \subfig[0.32]{results/Push-MeanContactTime-Hand-Overall-Means}
+  \subfig[0.32]{results/Push-CompletionTime}
+  \subfig[0.32]{results/Push-ContactsCount}
+  \subfig[0.32]{results/Push-MeanContactTime}
 \end{subfigs}

4-manipulation/visual-hand/3-2-grasp.tex

@@ -3,18 +3,18 @@
 
 \paragraph{Completion Time}
 
-On the time to complete a trial, there was one statistically significant effect %
-of \factor{Target} (\anova{7}{2868}{37.2}, \pinf{0.001}) %
-but not of \factor{Hand} (\anova{5}{2868}{1.8}, \p{0.1}, see \figref{results/Grasp-CompletionTime-Hand-Overall-Means}).
+On the time to complete a trial, there was one statistically significant effect
+of \factor{Target} (\anova{7}{3385}{34.3}, \pinf{0.001})
+but not of \factor{Hand} (\anova{5}{3385}{1.7}, \p{0.1}).
 Targets on the back and the left (\level{B}, \level{LB}, and \level{L}) were slower than targets on the front (\level{LF}, \level{F}, and \level{RF}, \p{0.003}) {except for} \level{RB} (back-right) which was also fast.
 
 \paragraph{Contacts}
 
-On the number of contacts, there were two statistically significant effects: %
-\factor{Hand} (\anova{5}{2868}{5.2}, \pinf{0.001}, see \figref{results/Grasp-ContactsCount-Hand-Overall-Means}) %
-and \factor{Target} (\anova{7}{2868}{21.2}, \pinf{0.001}).
+On the number of contacts, there were two statistically significant effects:
+\factor{Hand} (\anova{5}{3385}{4.9}, \pinf{0.001}, see \figref{results/Grasp-ContactsCount})
+and \factor{Target} (\anova{7}{3385}{20.0}, \pinf{0.001}).
 
-Less contacts were made with \level{Tips} than with \level{None} (\percent{-13}, \p{0.02}) and \level{Occlusion} (\percent{-15}, \p{0.004});
+Fewer contacts were made with \level{Tips} than with \level{None} (\percent{-13}, \p{0.02}) and \level{Occlusion} (\percent{-15}, \p{0.004});
 and less with \level{Mesh} than with \level{None} (\percent{-15}, \p{0.006}) and \level{Occlusion} (\percent{-17}, \p{0.001}).
 This result suggests that having no visible visual hand increased the number of failed grasps or cube drops.
 But, surprisingly, only \level{Tips} and \level{Mesh} were statistically significantly better, not \level{Contour} nor \level{Skeleton}.
@@ -23,9 +23,9 @@ Targets on the back and left were more difficult (\level{B}, \level{LB}, and \le
 
 \paragraph{Time per Contact}
 
-On the mean time spent on each contact, there were two statistically significant effects: %
-\factor{Hand} (\anova{5}{2868}{9.6}, \pinf{0.001}, see \figref{results/Grasp-MeanContactTime-Hand-Overall-Means}) %
-and \factor{Target} (\anova{7}{2868}{5.6}, \pinf{0.001}).
+On the mean time spent on each contact, there were two statistically significant effects:
+\factor{Hand} (\anova{5}{3385}{9.1}, \pinf{0.001}, see \figref{results/Grasp-MeanContactTime})
+and \factor{Target} (\anova{7}{3385}{5.4}, \pinf{0.001}).
 
 It was shorter with \level{None} than with \level{Tips} (\percent{-15}, \pinf{0.001}), \level{Skeleton} (\percent{-11}, \p{0.001}) and \level{Mesh} (\percent{-11}, \p{0.001});
 shorter with \level{Occlusion} than with \level{Tips} (\percent{-10}, \pinf{0.001}), \level{Skeleton} (\percent{-8}, \p{0.05}), and \level{Mesh} (\percent{-8}, \p{0.04});
@@ -38,15 +38,16 @@ This time was the shortest on the front \level{F} than on the other target volum
 \paragraph{Grip Aperture}
 
 On the average distance between the thumb's fingertip and the other fingertips during grasping, there were two
-statistically significant effects: %
-\factor{Hand} (\anova{5}{2868}{35.8}, \pinf{0.001}, see \figref{results/Grasp-GripAperture-Hand-Overall-Means}) %
-and \factor{Target} (\anova{7}{2868}{3.7}, \pinf{0.001}).
+statistically significant effects:
+\factor{Hand} (\anova{5}{19}{6.7}, \pinf{0.001}, see \figref{results/Grasp-GripAperture})
+and \factor{Target} (\anova{7}{3270}{4.1}, \pinf{0.001}).
+\footnote{Note that the best converging \LMM (with the lowest Akaike Information Criterion value) had a by-participant random intercept (like all the other models in this study) and a by-participant random slope for the \factor{Hand} factor. The results reported are from this model, which explains the different degrees of freedom from the other models.}
 
-It was shorter with \level{None} than with \level{Occlusion} (\pinf{0.001}), \level{Tips} (\pinf{0.001}), \level{Contour} (\pinf{0.001}), \level{Skeleton} (\pinf{0.001}) and \level{Mesh} (\pinf{0.001});
-shorter with \level{Tips} than with \level{Occlusion} (\p{0.008}), \level{Contour} (\p{0.006}) and \level{Mesh} (\pinf{0.001});
-and shorter with \level{Skeleton} than with \level{Mesh} (\pinf{0.001}).
+It was shorter with \level{None} than with \level{Occlusion} (\pinf{0.001}), \level{Contour} (\pinf{0.001}), \level{Skeleton} (\pinf{0.001}) and \level{Mesh} (\pinf{0.001}).
+%shorter with \level{Tips} than with \level{Occlusion} (\p{0.008}), \level{Contour} (\p{0.006}) and \level{Mesh} (\pinf{0.001});
+%and shorter with \level{Skeleton} than with \level{Mesh} (\pinf{0.001}).
 This result is an evidence of the lack of confidence of participants with no visual hand rendering: they grasped the cube more to secure it.
-The \level{Mesh} rendering seemed to have provided the most confidence to participants, maybe because it was the closest to the real hand.
+%The \level{Mesh} rendering seemed to have provided the most confidence to participants, maybe because it was the closest to the real hand.
 
 The \response{Grip Aperture} was longer on the right-front (\level{RF}) target volume, indicating a higher confidence, than on back and side targets (\level{R}, \level{RB}, \level{B}, \level{L}, \p{0.03}).
 
@@ -54,14 +55,11 @@ The \response{Grip Aperture} was longer on the right-front (\level{RF}) target v
     Geometric means with bootstrap \percent{95} \CI
     and Tukey's \HSD pairwise comparisons: *** is \pinf{0.001}, ** is \pinf{0.01}, and * is \pinf{0.05}.
   ][
-  \item Time to complete a trial.
   \item Number of contacts with the cube.
   \item Time spent on each contact.
   \item Distance between thumb and the other fingertips when grasping.
   ]
-  \subfig[0.4]{results/Grasp-CompletionTime-Hand-Overall-Means}
-  \subfig[0.4]{results/Grasp-ContactsCount-Hand-Overall-Means}
-  \par
-  \subfig[0.4]{results/Grasp-MeanContactTime-Hand-Overall-Means}
-  \subfig[0.4]{results/Grasp-GripAperture-Hand-Overall-Means}
+  \subfig[0.32]{results/Grasp-ContactsCount}
+  \subfig[0.32]{results/Grasp-MeanContactTime}
+  \subfig[0.32]{results/Grasp-GripAperture}
 \end{subfigs}

4-manipulation/visual-hand/3-3-ranks.tex

@@ -3,7 +3,7 @@
 
 \figref{results_ranks} shows the ranking of each visual \factor{Hand} rendering for the \level{Push} and \level{Grasp} tasks.
 Friedman tests indicated that both ranking had statistically significant differences (\pinf{0.001}).
-Pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment were then used on both ranking results (\secref{metrics}):
+Pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment were then used on both ranking results:
 
 \begin{itemize}
   \item \response{Push task ranking}: \level{Occlusion} was ranked lower than \level{Contour} (\p{0.005}), \level{Skeleton} (\p{0.02}), and \level{Mesh} (\p{0.03});
@@ -21,6 +21,6 @@ Pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment were then us
   \item Push task ranking.
   \item Grasp task ranking.
   ]
-  \subfig[0.4]{results/Ranks-Push}
-  \subfig[0.4]{results/Ranks-Grasp}
+  \subfig[0.32]{results/Ranks-Push}
+  \subfig[0.32]{results/Ranks-Grasp}
 \end{subfigs}

4-manipulation/visual-hand/3-4-questions.tex

@@ -3,7 +3,7 @@
 
 \figref{results_questions} presents the questionnaire results for each visual hand rendering.
 Friedman tests indicated that all questions had statistically significant differences (\pinf{0.001}).
-Pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment were then used each question results (\secref{metrics}):
+Pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment were then used each question results:
 \begin{itemize}
   \item \response{Difficulty}: \level{Occlusion} was considered more difficult than \level{Contour} (\p{0.02}), \level{Skeleton} (\p{0.01}), and \level{Mesh} (\p{0.03}).
   \item \response{Fatigue}: \level{None} was found more fatiguing than \level{Mesh} (\p{0.04}); And \level{Occlusion} more than \level{Skeleton} (\p{0.02}) and \level{Mesh} (\p{0.02}).
@@ -24,12 +24,11 @@ Each visual hand rendering, except for \level{Occlusion}, had simultaneously rec
     Lower is better for \textbf{(a)} difficulty and \textbf{(b)} fatigue.
     Higher is better for \textbf{(d)} performance, \textbf{(d)} precision, \textbf{(e)} efficiency, and \textbf{(f)} rating.
   ]
-  \subfig[0.4]{results/Question-Difficulty}
-  \subfig[0.4]{results/Question-Fatigue}
+  \subfig[0.32]{results/Question-Difficulty}
+  \subfig[0.32]{results/Question-Fatigue}
+  \subfig[0.32]{results/Question-Precision}
   \par
-  \subfig[0.4]{results/Question-Precision}
-  \subfig[0.4]{results/Question-Performance}
-  \par
-  \subfig[0.4]{results/Question-Efficiency}
-  \subfig[0.4]{results/Question-Rating}
+  \subfig[0.32]{results/Question-Performance}
+  \subfig[0.32]{results/Question-Efficiency}
+  \subfig[0.32]{results/Question-Rating}
 \end{subfigs}

4-manipulation/visual-hand/4-discussion.tex

@@ -3,14 +3,14 @@
 
 We evaluated six visual hand renderings, as described in \secref{hands}, displayed on top of the real hand, in two virtual object manipulation tasks in \AR.
 
-During the \level{Push} task, the \level{Skeleton} hand rendering was the fastest (\figref{results/Push-CompletionTime-Hand-Overall-Means}), as participants employed fewer and longer contacts to adjust the cube inside the target volume (\figref{results/Push-ContactsCount-Hand-Overall-Means} and \figref{results/Push-MeanContactTime-Hand-Overall-Means}).
+During the \level{Push} task, the \level{Skeleton} hand rendering was the fastest (\figref{results/Push-CompletionTime}), as participants employed fewer and longer contacts to adjust the cube inside the target volume (\figref{results/Push-ContactsCount} and \figref{results/Push-MeanContactTime}).
 Participants consistently used few and continuous contacts for all visual hand renderings (Fig. 3b), with only less than ten trials, carried out by two participants, quickly completed with multiple discrete touches.
-However, during the \level{Grasp} task, despite no difference in \response{Completion Time}, providing no visible hand rendering (\level{None} and \level{Occlusion} renderings) led to more failed grasps or cube drops (\figref{results/Grasp-CompletionTime-Hand-Overall-Means} and \figref{results/Grasp-MeanContactTime-Hand-Overall-Means}).
+However, during the \level{Grasp} task, despite no difference in \response{Completion Time}, providing no visible hand rendering (\level{None} and \level{Occlusion} renderings) led to more failed grasps or cube drops (\figref{results/Grasp-ContactsCount} and \figref{results/Grasp-MeanContactTime}).
 Indeed, participants found the \level{None} and \level{Occlusion} renderings less effective (\figref{results/Ranks-Grasp}) and less precise (\figref{results_questions}).
 To understand whether the participants' previous experience might have played a role, we also carried out an additional statistical analysis considering \VR experience as an additional between-subjects factor, \ie \VR novices vs. \VR experts (\enquote{I use it every week}, see \secref{participants}).
 We found no statistically significant differences when comparing the considered metrics between \VR novices and experts.
 
-All visual hand renderings showed \response{Grip Apertures} close to the size of the virtual cube, except for the \level{None} rendering (\figref{results/Grasp-GripAperture-Hand-Overall-Means}), with which participants applied stronger grasps, \ie less distance between the fingertips.
+All visual hand renderings showed \response{Grip Apertures} close to the size of the virtual cube, except for the \level{None} rendering (\figref{results/Grasp-GripAperture}), with which participants applied stronger grasps, \ie less distance between the fingertips.
 Having no visual hand rendering, but only the reaction of the cube to the interaction as feedback, made participants less confident in their grip.
 This result contrasts with the wrongly estimated grip apertures observed by \textcite{al-kalbani2016analysis} in an exocentric VST-AR setup.
 Also, while some participants found the absence of visual hand rendering more natural, many of them commented on the importance of having feedback on the tracking of their hands, as observed by \textcite{xiao2018mrtouch} in a similar immersive OST-AR setup.