Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)

We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overc...

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Autores principales: Laal, Sepehr, Vasilyev, Paul, Pearson, Sean, Aboy, Mateo, McNames, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739070/
https://www.ncbi.nlm.nih.gov/pubmed/36502075
http://dx.doi.org/10.3390/s22239378
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author Laal, Sepehr
Vasilyev, Paul
Pearson, Sean
Aboy, Mateo
McNames, James
author_facet Laal, Sepehr
Vasilyev, Paul
Pearson, Sean
Aboy, Mateo
McNames, James
author_sort Laal, Sepehr
collection PubMed
description We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant technologies. Our results demonstrate this system often attains an estimated orientation error of less than 1° and a position error of less than 4 [Formula: see text] as compared to a robotic arm. This demonstrates that SLAM’s accuracy is adequate for many practical applications for tracking human kinematics.
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spelling pubmed-97390702022-12-11 Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM) Laal, Sepehr Vasilyev, Paul Pearson, Sean Aboy, Mateo McNames, James Sensors (Basel) Article We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant technologies. Our results demonstrate this system often attains an estimated orientation error of less than 1° and a position error of less than 4 [Formula: see text] as compared to a robotic arm. This demonstrates that SLAM’s accuracy is adequate for many practical applications for tracking human kinematics. MDPI 2022-12-01 /pmc/articles/PMC9739070/ /pubmed/36502075 http://dx.doi.org/10.3390/s22239378 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Laal, Sepehr
Vasilyev, Paul
Pearson, Sean
Aboy, Mateo
McNames, James
Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)
title Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)
title_full Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)
title_fullStr Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)
title_full_unstemmed Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)
title_short Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)
title_sort feasibility of tracking human kinematics with simultaneous localization and mapping (slam)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739070/
https://www.ncbi.nlm.nih.gov/pubmed/36502075
http://dx.doi.org/10.3390/s22239378
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