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Erwan Normand
2025-04-06 12:24:29 +02:00
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2
2-related-work/1-haptic-hand.tex
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@@ -91,7 +91,7 @@ As illustrated in \figref{sensorimotor_continuum}, \textcite{jones2006human} del
\item \emph{Gestures}, or non-prehensible skilled movements, are motor activities without constant contact with an object. Examples include pointing at a target, typing on a keyboard, accompanying speech with gestures, or signing in sign language \cite{yoon2020evaluating}.
\end{itemize}
\fig[0.65]{sensorimotor_continuum}{ The sensorimotor continuum of the hand function proposed by and adapted from \textcite{jones2006human}.}[%
\fig[0.65]{sensorimotor_continuum}{ The sensorimotor continuum of the hand function proposed by and adapted from \textcite{jones2006human}.}[
Functions of the hand are classified into four categories based on the relative importance of sensory and motor components.
\protect\footnotemark
]

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3-perception/vhar-textures/3-results.tex
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@@ -83,12 +83,10 @@ The first dimension was similar to the rankings (\figref{results/ranking_mean_ci
It seems that the second dimension opposed textures that were perceived as hard with those perceived as softer, as also reported by participants.
Stiffness is indeed an important perceptual dimension of a material (\secref[related_work]{hardness}).% \cite{okamoto2013psychophysical,culbertson2014modeling}.
\fig[0.6]{results/matching_correspondence_analysis}{
Correspondence analysis of the confusion matrix of the \level{Matching} task.
}[
The closer the haptic and visual textures are, the more similar they were judged. %
The first dimension (horizontal axis) explains \percent{60} of the variance, the second dimension (vertical axis) explains \percent{30} of the variance.
The confusion matrix is \figref{results/matching_confusion_matrix}.
\fig[1]{results/matching_correspondence_analysis}{Correspondence analysis of the confusion matrix of the \level{Matching} task.}[
The closer the haptic and visual textures are, the more similar they were judged.
The first dimension (horizontal axis) explains \percent{60} of the variance, the second dimension (vertical axis) explains \percent{29} of the variance.
The confusion matrix is shown in \figref{results/matching_confusion_matrix}.
]
\paragraph{Hierarchical Clustering}
@@ -102,15 +100,15 @@ It also shows that the participants compared and ranked the haptic textures duri
The five identified visual texture clusters were: "Roughest" \{\level{Metal Mesh}\}; "Rougher" \{\level{Sandpaper~100}, \level{Brick~2}, \level{Velcro Hooks}\}; "Medium" \{\level{Cork}, \level{Plastic Mesh~1}\}; "Smoother" \{\level{Sandpaper~320}, \level{Terra Cotta}\}; "Smoothest" \{\level{Coffee Filter}\} (\figref{results/clusters_visual}).
They are also easily identifiable on the visual ranking results, which also made it possible to name them.
\begin{subfigs}{results_clusters}{Dendrograms of the hierarchical clusterings of the \level{Matching} task confusion matrix.}[
\begin{subfigs}{results_clusters}{Dendrograms of the hierarchical clusterings of the confusion matrix of the \level{Matching} task.}[
Done with the Euclidean distance and the Ward's method on squared distance.
The height of the dendrograms represents the distance between the clusters.
][%
][
\item For the haptic textures.
\item For the visual textures.
]
\subfig[0.45]{results/clusters_haptic}
\subfig[0.45]{results/clusters_visual}
\subfig[0.48]{results/clusters_haptic}
\subfig[0.48]{results/clusters_visual}
\end{subfigs}
\paragraph{Confusion Matrices of Clusters}
@@ -140,7 +138,7 @@ A non-parametric \ANOVA on \ART models were used for the \response{Difficulty} a
The other question results were analyzed using Wilcoxon signed-rank tests, with Holm-Bonferroni adjustment.
The results are shown as mean $\pm$ standard deviation.
On \response{Difficulty}, there were statistically significant effects of \factor{Task} (\anova{1}{57}{13}, \pinf{0.001}) and of \factor{Modality} (\anova{1}{57}{8}, \p{0.007}), but no interaction effect. % \factor{Task} \x \factor{Modality} (\anova{1}{57}{2}, \ns).
On \response{Difficulty}, there were statistically significant effects of \factor{Task} (\anova{1}{57}{13}, \pinf{0.001}) and of \factor{Modality} (\anova{1}{57}{8}, \p{0.007}), but no interaction effect \factor{Task} \x \factor{Modality} (\anova{1}{57}{2}, \ns).
The \level{Ranking} task was found easier (\num{2.9 \pm 1.2}) than the \level{Matching} task (\num{3.9 \pm 1.5}), and the Haptic textures were found easier to discriminate (\num{3.0 \pm 1.3}) than the Visual ones (\num{3.8 \pm 1.5}).
Both haptic and visual textures were judged moderately realistic for both tasks (\num{4.2 \pm 1.3}), with no statistically significant effect of \factor{Task}, \factor{Modality} or their interaction on \response{Realism}.
@@ -151,10 +149,10 @@ The coherence of the texture pairs was considered moderate (\num{4.6 \pm 1.2}) a
Pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment: * is \pinf{0.05}, ** is \pinf{0.01} and *** is \pinf{0.001}.
Lower is better for Difficulty and Uncomfortable; higher is better for Realism and Textures Match.
][
\item By modality.
\item By task.
\item By \factor{Modality}.
\item By \factor{Task}.
]
\subfigsheight{70mm}
\subfig{results/questions_modalities}%
\subfig{results/questions_tasks}%
\subfigsheight{75mm}
\subfig{results/questions_modalities}
\subfig{results/questions_tasks}
\end{subfigs}

2
3-perception/vhar-textures/5-conclusion.tex
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@@ -22,7 +22,7 @@ In the next part, we will propose to improve the direct manipulation with the ha
Erwan Normand, Claudio Pacchierotti, Eric Marchand, and Maud Marchal. \enquote{Augmenting the Texture Perception of Tangible Surfaces in Augmented Reality using Vibrotactile Haptic Stimuli}. In: \textit{EuroHaptics}. Lille, France, July 2024. pp. 469--484.
\fig[0.5]{experiment/use_case}{
\fig[0.65]{experiment/use_case}{
Illustration of the texture augmentation in \AR through an interior design scenario.
}[
A user wearing an \AR headset and a wearable vibrotactile haptic device worn on their index is applying different virtual visuo-haptic textures to a real wall to compare them visually and by touch.

2
3-perception/xr-perception/1-introduction.tex
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@@ -26,6 +26,6 @@ We then present the results obtained, discuss them, and outline recommendations
\fig[0.55]{teaser/teaser2}{
Vibrotactile textures were rendered in real time on a real surface using a wearable vibrotactile device worn on the finger.
}[%
}[
Participants explored this haptic roughness augmentation with (\level{Real}) their real hand alone, (\level{Mixed}) a realistic virtual hand overlay in \AR, and (\level{Virtual}) the same virtual hand in \VR.
]

2
3-perception/xr-perception/3-experiment.tex
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@@ -9,7 +9,7 @@ In order not to influence the perception, as vision is an important source of in
\begin{subfigs}{renderings}{
The three visual rendering conditions and the experimental procedure of the \TIFC psychophysical study.
}[%
}[
During a trial, two tactile textures were rendered on the augmented area of the paper sheet (black rectangle) for \qty{3}{\s} each, one after the other, then the participant chose which one was the roughest.
The visual rendering stayed the same during the trial.
The pictures are captured directly from the Microsoft HoloLens 2 headset.

9
3-perception/xr-perception/4-results.tex
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@@ -37,7 +37,7 @@ All pairwise differences were statistically significant.
\subsubsection{Response Time}
\label{response_time}
A \LMM \ANOVA with by-participant random slopes for \factor{Visual Rendering}, and a log transformation (as \response{Response Time} measures were gamma distributed) indicated a statistically significant effect on \response{Response Time} of \factor{Visual Rendering} (\anova{2}{18}{6.2}, \p{0.009}, \figref{results/trial_response_times}).
A \LMM \ANOVA with by-participant random slopes for \factor{Visual Rendering}, and a log transformation (as \response{Response Time} measures were gamma distributed) indicated a statistically significant effect on \response{Response Time} of \factor{Visual Rendering} (\anova{2}{18}{6.2}, \p{0.009}, see \figref{results/trial_response_times}).
Reported response times are \GM.
Participants took longer on average to respond with the \level{Virtual} rendering (\geomean{1.65}{\s} \ci{1.59}{1.72}) than with the \level{Real} rendering (\geomean{1.38}{\s} \ci{1.32}{1.43}), which is the only statistically significant difference (\ttest{19}{0.3}, \p{0.005}).
The \level{Mixed} rendering was in between (\geomean{1.56}{\s} \ci{1.49}{1.63}).
@@ -47,17 +47,17 @@ The \level{Mixed} rendering was in between (\geomean{1.56}{\s} \ci{1.49}{1.63}).
The frames analyzed were those in which the participants actively touched the comparison textures with a finger speed greater than \SI{1}{\mm\per\second}.
A \LMM \ANOVA with by-participant random slopes for \factor{Visual Rendering} indicated only one statistically significant effect on the total distance traveled by the finger in a trial of \factor{Visual Rendering} (\anova{2}{18}{3.9}, \p{0.04}, \figref{results/trial_distances}).
A \LMM \ANOVA with by-participant random slopes for \factor{Visual Rendering} indicated only one statistically significant effect on the total distance traveled by the finger in a trial of \factor{Visual Rendering} (\anova{2}{18}{3.9}, \p{0.04}, see \figref{results/trial_distances}).
On average, participants explored a larger distance with the \level{Real} rendering (\geomean{20.0}{\cm} \ci{19.4}{20.7}) than with \level{Virtual} rendering (\geomean{16.5}{\cm} \ci{15.8}{17.1}), which is the only statistically significant difference (\ttest{19}{1.2}, \p{0.03}), with the \level{Mixed} rendering (\geomean{17.4}{\cm} \ci{16.8}{18.0}) in between.
Another \LMM \ANOVA with by-trial and by-participant random intercepts but no random slopes indicated only one statistically significant effect on \response{Finger Speed} of \factor{Visual Rendering} (\anova{2}{2142}{2.0}, \pinf{0.001}, \figref{results/trial_speeds}).
Another \LMM \ANOVA with by-trial and by-participant random intercepts but no random slopes indicated only one statistically significant effect on \response{Finger Speed} of \factor{Visual Rendering} (\anova{2}{2142}{2.0}, \pinf{0.001}, see \figref{results/trial_speeds}).
On average, the textures were explored with the highest speed with the \level{Real} rendering (\geomean{5.12}{\cm\per\second} \ci{5.08}{5.17}), the lowest with the \level{Virtual} rendering (\geomean{4.40}{\cm\per\second} \ci{4.35}{4.45}), and the \level{Mixed} rendering (\geomean{4.67}{\cm\per\second} \ci{4.63}{4.71}) in between.
All pairwise differences were statistically significant: \level{Real} \vs \level{Virtual} (\ttest{19}{1.17}, \pinf{0.001}), \level{Real} \vs \level{Mixed} (\ttest{19}{1.10}, \pinf{0.001}), and \level{Mixed} \vs \level{Virtual} (\ttest{19}{1.07}, \p{0.02}).
This means that within the same time window on the same surface, participants explored the comparison texture on average at a greater distance and at a higher speed when in the \RE without visual representation of the hand (\level{Real} condition) than when in \VR (\level{Virtual} condition).
\begin{subfigs}{results_finger}{Results of the performance metrics for the rendering condition.}[
Boxplots and geometric means with bootstrap \percent{95} \CI, with Tukey's \HSD pairwise comparisons: * is \pinf{0.05}, ** is \pinf{0.01} and *** is \pinf{0.001}.
Boxplots and geometric means with bootstrap \percent{95} \CI and Tukey's \HSD pairwise comparisons: * is \pinf{0.05}, ** is \pinf{0.01} and *** is \pinf{0.001}.
][
\item Response time at the end of a trial.
\item Distance travelled by the finger in a trial.
@@ -135,4 +135,3 @@ Participants were mixed between feeling the vibrations on the surface or on the
%
% (Right) Load Index (NASA-TLX) questionnaire (lower values are better).
%}