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Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment

Motion analysis is an area with several applications for health, sports, and entertainment. The high cost of state-of-the-art equipment in the health field makes it unfeasible to apply this technique in the clinics’ routines. In this vein, RGB-D and RGB equipment, which have joint tracking tools, ar...

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Autores principales: Lafayette, Thiago Buarque de Gusmão, Kunst, Victor Hugo de Lima, Melo, Pedro Vanderlei de Sousa, Guedes, Paulo de Oliveira, Teixeira, João Marcelo Xavier Natário, de Vasconcelos, Cínthia Rodrigues, Teichrieb, Veronica, da Gama, Alana Elza Fontes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824231/
https://www.ncbi.nlm.nih.gov/pubmed/36616603
http://dx.doi.org/10.3390/s23010003
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author Lafayette, Thiago Buarque de Gusmão
Kunst, Victor Hugo de Lima
Melo, Pedro Vanderlei de Sousa
Guedes, Paulo de Oliveira
Teixeira, João Marcelo Xavier Natário
de Vasconcelos, Cínthia Rodrigues
Teichrieb, Veronica
da Gama, Alana Elza Fontes
author_facet Lafayette, Thiago Buarque de Gusmão
Kunst, Victor Hugo de Lima
Melo, Pedro Vanderlei de Sousa
Guedes, Paulo de Oliveira
Teixeira, João Marcelo Xavier Natário
de Vasconcelos, Cínthia Rodrigues
Teichrieb, Veronica
da Gama, Alana Elza Fontes
author_sort Lafayette, Thiago Buarque de Gusmão
collection PubMed
description Motion analysis is an area with several applications for health, sports, and entertainment. The high cost of state-of-the-art equipment in the health field makes it unfeasible to apply this technique in the clinics’ routines. In this vein, RGB-D and RGB equipment, which have joint tracking tools, are tested with portable and low-cost solutions to enable computational motion analysis. The recent release of Google MediaPipe, a joint inference tracking technique that uses conventional RGB cameras, can be considered a milestone due to its ability to estimate depth coordinates in planar images. In light of this, this work aims to evaluate the measurement of angular variation from RGB-D and RGB sensor data against the Qualisys Tracking Manager gold standard. A total of 60 recordings were performed for each upper and lower limb movement in two different position configurations concerning the sensors. Google’s MediaPipe usage obtained close results compared to Kinect V2 sensor in the inherent aspects of absolute error, RMS, and correlation to the gold standard, presenting lower dispersion values and error metrics, which is more positive. In the comparison with equipment commonly used in physical evaluations, MediaPipe had an error within the error range of short- and long-arm goniometers.
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spelling pubmed-98242312023-01-08 Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment Lafayette, Thiago Buarque de Gusmão Kunst, Victor Hugo de Lima Melo, Pedro Vanderlei de Sousa Guedes, Paulo de Oliveira Teixeira, João Marcelo Xavier Natário de Vasconcelos, Cínthia Rodrigues Teichrieb, Veronica da Gama, Alana Elza Fontes Sensors (Basel) Article Motion analysis is an area with several applications for health, sports, and entertainment. The high cost of state-of-the-art equipment in the health field makes it unfeasible to apply this technique in the clinics’ routines. In this vein, RGB-D and RGB equipment, which have joint tracking tools, are tested with portable and low-cost solutions to enable computational motion analysis. The recent release of Google MediaPipe, a joint inference tracking technique that uses conventional RGB cameras, can be considered a milestone due to its ability to estimate depth coordinates in planar images. In light of this, this work aims to evaluate the measurement of angular variation from RGB-D and RGB sensor data against the Qualisys Tracking Manager gold standard. A total of 60 recordings were performed for each upper and lower limb movement in two different position configurations concerning the sensors. Google’s MediaPipe usage obtained close results compared to Kinect V2 sensor in the inherent aspects of absolute error, RMS, and correlation to the gold standard, presenting lower dispersion values and error metrics, which is more positive. In the comparison with equipment commonly used in physical evaluations, MediaPipe had an error within the error range of short- and long-arm goniometers. MDPI 2022-12-20 /pmc/articles/PMC9824231/ /pubmed/36616603 http://dx.doi.org/10.3390/s23010003 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
Lafayette, Thiago Buarque de Gusmão
Kunst, Victor Hugo de Lima
Melo, Pedro Vanderlei de Sousa
Guedes, Paulo de Oliveira
Teixeira, João Marcelo Xavier Natário
de Vasconcelos, Cínthia Rodrigues
Teichrieb, Veronica
da Gama, Alana Elza Fontes
Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment
title Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment
title_full Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment
title_fullStr Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment
title_full_unstemmed Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment
title_short Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment
title_sort validation of angle estimation based on body tracking data from rgb-d and rgb cameras for biomechanical assessment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824231/
https://www.ncbi.nlm.nih.gov/pubmed/36616603
http://dx.doi.org/10.3390/s23010003
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