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Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing

Augmented reality (AR) Head-Mounted Displays (HMDs) are emerging as the most efficient output medium to support manual tasks performed under direct vision. Despite that, technological and human-factor limitations still hinder their routine use for aiding high-precision manual tasks in the periperson...

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Autores principales: Condino, Sara, Fida, Benish, Carbone, Marina, Cercenelli, Laura, Badiali, Giovanni, Ferrari, Vincenzo, Cutolo, Fabrizio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146390/
https://www.ncbi.nlm.nih.gov/pubmed/32183212
http://dx.doi.org/10.3390/s20061612
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author Condino, Sara
Fida, Benish
Carbone, Marina
Cercenelli, Laura
Badiali, Giovanni
Ferrari, Vincenzo
Cutolo, Fabrizio
author_facet Condino, Sara
Fida, Benish
Carbone, Marina
Cercenelli, Laura
Badiali, Giovanni
Ferrari, Vincenzo
Cutolo, Fabrizio
author_sort Condino, Sara
collection PubMed
description Augmented reality (AR) Head-Mounted Displays (HMDs) are emerging as the most efficient output medium to support manual tasks performed under direct vision. Despite that, technological and human-factor limitations still hinder their routine use for aiding high-precision manual tasks in the peripersonal space. To overcome such limitations, in this work, we show the results of a user study aimed to validate qualitatively and quantitatively a recently developed AR platform specifically conceived for guiding complex 3D trajectory tracing tasks. The AR platform comprises a new-concept AR video see-through (VST) HMD and a dedicated software framework for the effective deployment of the AR application. In the experiments, the subjects were asked to perform 3D trajectory tracing tasks on 3D-printed replica of planar structures or more elaborated bony anatomies. The accuracy of the trajectories traced by the subjects was evaluated by using templates designed ad hoc to match the surface of the phantoms. The quantitative results suggest that the AR platform could be used to guide high-precision tasks: on average more than 94% of the traced trajectories stayed within an error margin lower than 1 mm. The results confirm that the proposed AR platform will boost the profitable adoption of AR HMDs to guide high precision manual tasks in the peripersonal space.
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spelling pubmed-71463902020-04-15 Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing Condino, Sara Fida, Benish Carbone, Marina Cercenelli, Laura Badiali, Giovanni Ferrari, Vincenzo Cutolo, Fabrizio Sensors (Basel) Article Augmented reality (AR) Head-Mounted Displays (HMDs) are emerging as the most efficient output medium to support manual tasks performed under direct vision. Despite that, technological and human-factor limitations still hinder their routine use for aiding high-precision manual tasks in the peripersonal space. To overcome such limitations, in this work, we show the results of a user study aimed to validate qualitatively and quantitatively a recently developed AR platform specifically conceived for guiding complex 3D trajectory tracing tasks. The AR platform comprises a new-concept AR video see-through (VST) HMD and a dedicated software framework for the effective deployment of the AR application. In the experiments, the subjects were asked to perform 3D trajectory tracing tasks on 3D-printed replica of planar structures or more elaborated bony anatomies. The accuracy of the trajectories traced by the subjects was evaluated by using templates designed ad hoc to match the surface of the phantoms. The quantitative results suggest that the AR platform could be used to guide high-precision tasks: on average more than 94% of the traced trajectories stayed within an error margin lower than 1 mm. The results confirm that the proposed AR platform will boost the profitable adoption of AR HMDs to guide high precision manual tasks in the peripersonal space. MDPI 2020-03-13 /pmc/articles/PMC7146390/ /pubmed/32183212 http://dx.doi.org/10.3390/s20061612 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Condino, Sara
Fida, Benish
Carbone, Marina
Cercenelli, Laura
Badiali, Giovanni
Ferrari, Vincenzo
Cutolo, Fabrizio
Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing
title Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing
title_full Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing
title_fullStr Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing
title_full_unstemmed Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing
title_short Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing
title_sort wearable augmented reality platform for aiding complex 3d trajectory tracing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146390/
https://www.ncbi.nlm.nih.gov/pubmed/32183212
http://dx.doi.org/10.3390/s20061612
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