Simpler section reference labels
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\section{Introduction}
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\label{sec:introduction}
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\label{introduction}
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When we look at the surface of an everyday object, we then touch it to confirm or contrast our initial visual impression and to estimate the properties of the object~\autocite{ernst2002humans}.
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\section{User Study}
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\label{sec:experiment}
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\label{experiment}
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\begin{subfigs}{setup}{%
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User Study.
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}[%
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}[%
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\item The nine visuo-haptic textures used in the user study, selected from the HaTT database~\autocite{culbertson2014one}. %
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The texture names were never shown, so as to prevent the use of the user's visual or haptic memory of the textures.
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\item Experimental setup. %
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\item First person view of the user study, as seen through the immersive AR headset HoloLens~2. %
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The visual texture overlays are statically displayed on the surfaces, allowing the user to move around to view them from different angles. %
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The haptic roughness texture is generated based on HaTT data-driven texture models and finger speed, and it is rendered on the middle index phalanx as it slides on the considered surface.%
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]
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]
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\subfig[0.32]{experiment/textures}%
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\subfig[0.32]{experiment/setup}%
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\subfig[0.32]{experiment/view}%
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@@ -28,7 +28,7 @@ Our objective is to assess which haptic textures were associated with which visu
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\subsection{The textures}
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\label{sec::textures}
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\label{textures}
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The 100 visuo-haptic texture pairs of the HaTT database~\autocite{culbertson2014one} were preliminary tested and compared using AR and vibrotactile haptic feedback on the finger on a tangible surface.
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@@ -40,7 +40,7 @@ All these visual and haptic textures are isotropic: their rendering (appearance
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\subsection{Apparatus}
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\label{sec::apparatus}
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\label{apparatus}
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\figref{setup} shows the experimental setup (middle) and the first person view (right) of the user study.
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@@ -70,7 +70,7 @@ The user study was held in a quiet room with no windows, with one light source o
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\subsection{Procedure and Collected Data}
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\label{sec::procedure}
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\label{procedure}
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Participants were first given written instructions about the experimental setup, the tasks, and the procedure of the user study.
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@@ -117,7 +117,7 @@ The user study took on average 1 hour to complete.
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\subsection{Participants}
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\label{sec::participants}
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\label{participants}
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Twenty participants took part to the user study (12 males, 7 females, 1 preferred not to say), aged between 20 and 60 years old (M=29.1, SD=9.4).
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@@ -135,7 +135,7 @@ They all signed an informed consent form before the user study.
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\subsection{Design}
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\label{sec::design}
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\label{design}
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The matching task was a single-factor within-subjects design, \textit{Visual Texture}, with the following levels:
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\section{Results}
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\label{sec:results}
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\label{results}
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\subsection{Textures Matching}
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\label{sec:results_matching}
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\label{results_matching}
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\subsubsection{Confusion Matrix}
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\label{sec:results_matching_confusion_matrix}
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\label{results_matching_confusion_matrix}
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\begin{subfigs}{results_matching_ranking}{%
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(Left) Confusion matrix of the matching task, with the presented visual textures as columns and the selected haptic texture in proportion as rows. %
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@@ -45,7 +45,7 @@ Another explanation could be that the participants had difficulties to estimate
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Indeed, many participants explained that they tried to identify or imagine the roughness of a given visual texture then to select the most plausible haptic texture, in terms of frequency and/or amplitude of vibrations.
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\subsubsection{Completion Time}
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\label{sec:results_matching_time}
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\label{results_matching_time}
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To verify that the difficulty with all the visual textures was the same on the matching task, the \textit{Completion Time} of a trial, \ie the time between the visual texture display and the haptic texture selection, was analyzed.
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%
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@@ -59,7 +59,7 @@ No statistical significant effect of \textit{Visual Texture} was found (\anova{8
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\subsection{Textures Ranking}
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\label{sec:results_ranking}
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\label{results_ranking}
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\figref{results_matching_ranking} (right) presents the results of the three rankings of the haptic textures alone, the visual textures alone, and the visuo-haptic texture pairs.
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@@ -83,7 +83,7 @@ These results indicate, with \figref{results_matching_ranking} (right), that the
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\subsection{Perceived Similarity of Visual and Haptic Textures}
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\label{sec:results_similarity}
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\label{results_similarity}
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\begin{subfigs}{results_similarity}{%
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(Left) Correspondence analysis of the matching task confusion matrix (see \figref{results_matching_ranking}, left).
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@@ -155,7 +155,7 @@ This shows that the participants consistently identified the roughness of each v
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\subsection{Questionnaire}
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\label{sec:results_questions}
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\label{results_questions}
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\begin{subfigs}{results_questions}{%
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Boxplots of the 7-item Likert scale question results (1=Not at all, 7=Extremely) %
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\section{Discussion}
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\label{sec:discussion}
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\label{discussion}
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In this study, we investigated the perception of visuo-haptic texture augmentation of tangible surfaces touched directly with the index fingertip, using visual texture overlays in AR and haptic roughness textures generated by a vibrotactile device worn on the middle index phalanx.
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\section{Conclusion}
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\label{sec:conclusion}
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\label{conclusion}
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\fig[0.6]{experiment/use_case}{%
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Illustration of the texture augmentation in AR through an interior design scenario. %
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\section{Introduction}
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\label{sec:introduction}
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\label{introduction}
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% Delivers the motivation for your paper. It explains why you did the work you did.
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\section{Visuo-Haptic Texture Rendering in Mixed Reality}
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\label{sec:method}
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\label{method}
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\figwide[1]{method/diagram}{%
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Diagram of the visuo-haptic texture rendering system.
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@@ -42,7 +42,7 @@ The system is composed of three main components: the pose estimation of the trac
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\subsection{Pose Estimation and Virtual Environment Alignment}
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\label{sec:virtual_real_alignment}
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\label{virtual_real_alignment}
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\begin{subfigs}{setup}{Visuo-haptic texture rendering system setup}[%
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\item HapCoil-One voice-coil actuator with a fiducial marker on top attached to a participant's right index finger. %
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@@ -95,7 +95,7 @@ To simulate a VR headset, a cardboard mask (with holes for sensors) is attached
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\subsection{Vibrotactile Signal Generation and Rendering}
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\label{sec:texture_generation}
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\label{texture_generation}
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A voice-coil actuator (HapCoil-One, Actronika) is used to display the vibrotactile signal, as it allows the frequency and amplitude of the signal to be controlled independently over time, covers a wide frequency range (\qtyrange{10}{1000}{\Hz}), and outputs the signal accurately with relatively low acceleration distortion\footnote{HapCoil-One specific characteristics are described in its data sheet: \url{https://web.archive.org/web/20240228161416/https://tactilelabs.com/wp-content/uploads/2023/11/HapCoil_One_datasheet.pdf}}.
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@@ -149,7 +149,7 @@ The tactile texture is described and rendered in this work as a one dimensional
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\subsection{System Latency}
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\label{sec:latency}
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\label{latency}
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%As shown in \figref{method/diagram} and described above, the system includes various haptic and visual sensors and rendering devices linked by software processes for image processing, 3D rendering and audio generation.
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%
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\section{User Study}
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\label{sec:experiment}
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\label{experiment}
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\begin{subfigswide}{renderings}{%
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The three visual rendering conditions and the experimental procedure of the two-alternative forced choice (2AFC) psychophysical study.
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\subsection{Participants}
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\label{sec:participants}
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\label{participants}
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Twenty participants were recruited for the study (16 males, 3 females, 1 prefer not to say), aged between 18 and 61 years old (\median{26}{}, \iqr{6.8}{}).
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%
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\subsection{Apparatus}
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\label{sec:apparatus}
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\label{apparatus}
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An experimental environment similar as \textcite{gaffary2017ar} was created to ensure a similar visual rendering in AR and VR (see \figref{renderings}).
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\subsection{Procedure}
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\label{sec:procedure}
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\label{procedure}
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Participants were first given written instructions about the experimental setup and procedure, the informed consent form to sign, and a demographic questionnaire.
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\subsection{Experimental Design}
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\label{sec:experimental_design}
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\label{experimental_design}
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The user study was a within-subjects design with two factors:
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\subsection{Collected Data}
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\label{sec:collected_data}
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\label{collected_data}
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For each trial, the \textit{Texture Choice} by the participant as the roughest of the pair was recorded.
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\section{Results}
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\label{sec:results}
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\label{results}
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\subsection{Trial Measures}
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\label{sec:results_trials}
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\label{results_trials}
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All measures from trials were analysed using linear mixed models (LMM) or generalised linear mixed models (GLMM) with \factor{Visual Rendering}, \factor{Amplitude Difference} and their interaction as within-participant factors, and by-participant random intercepts.
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\subsubsection{Discrimination Accuracy}
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\label{sec:discrimination_accuracy}
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\label{discrimination_accuracy}
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A GLMM was adjusted to the \response{Texture Choice} in the 2AFC vibrotactile texture roughness discrimination task, with by-participant random intercepts but no random slopes, and a probit link function (see \figref{results/trial_predictions}).
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\subsubsection{Response Time}
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\label{sec:response_time}
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\label{response_time}
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A LMM analysis of variance (AOV) 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 effects on \response{Response Time} of \factor{Visual Rendering} (\anova{2}{18}{6.2}, \p{0.009}, see \figref{results/trial_response_times}).
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\subsubsection{Finger Position and Speed}
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\label{sec:finger_position_speed}
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\label{finger_position_speed}
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The frames analysed were those in which the participants actively touched the comparison textures with a finger speed greater than \SI{1}{\mm\per\second}.
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\subsection{Questionnaires}
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\label{sec:questions}
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\label{questions}
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%\figref{results/question_heatmaps} shows the median and interquartile range (IQR) ratings to the questions in \tabref{questions} and to the NASA-TLX questionnaire.
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\section{Discussion}
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\label{sec:discussion}
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\label{discussion}
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%Interpret the findings in results, answer to the problem asked in the introduction, contrast with previous articles, draw possible implications. Give limitations of the study.
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\section{Conclusion}
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\label{sec:conclusion}
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\label{conclusion}
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%Summary of the research problem, method, main findings, and implications.
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