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Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities

In the search to enhance ergonomic risk assessments for upper limb work-related activities, this study introduced and validated the efficiency of an inertial motion capture system, paired with a specialized platform that digitalized the OCRA index. Conducted in a semi-controlled environment, the pro...

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Autores principales: Aqueveque, Pablo, Peña, Guisella, Gutiérrez, Manuel, Gómez, Britam, Germany, Enrique, Retamal, Gustavo, Ortega-Bastidas, Paulina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490628/
https://www.ncbi.nlm.nih.gov/pubmed/37688078
http://dx.doi.org/10.3390/s23177623
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author Aqueveque, Pablo
Peña, Guisella
Gutiérrez, Manuel
Gómez, Britam
Germany, Enrique
Retamal, Gustavo
Ortega-Bastidas, Paulina
author_facet Aqueveque, Pablo
Peña, Guisella
Gutiérrez, Manuel
Gómez, Britam
Germany, Enrique
Retamal, Gustavo
Ortega-Bastidas, Paulina
author_sort Aqueveque, Pablo
collection PubMed
description In the search to enhance ergonomic risk assessments for upper limb work-related activities, this study introduced and validated the efficiency of an inertial motion capture system, paired with a specialized platform that digitalized the OCRA index. Conducted in a semi-controlled environment, the proposed methodology was compared to traditional risk classification techniques using both inertial and optical motion capture systems. The inertial method encompassed 18 units in a Bluetooth Low Energy tree topology network for activity recording, subsequently analyzed for risk using the platform. Principal outcomes emphasized the optical system’s preeminence, aligning closely with the conventional technique. The optical system’s superiority was further evident in its alignment with the traditional method. Meanwhile, the inertial system followed closely, with an error margin of just ±0.098 compared to the optical system. Risk classification was consistent across all systems. The inertial system demonstrated strong performance metrics, achieving F1-scores of 0.97 and 1 for “risk” and “no risk” classifications, respectively. Its distinct advantage of portability was reinforced by participants’ feedback on its user-friendliness. The results highlight the inertial system’s potential, mirroring the precision of both traditional and optical methods and achieving a 65% reduction in risk assessment time. This advancement mitigates the need for intricate video setups, emphasizing its potential in ergonomic assessments.
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spelling pubmed-104906282023-09-09 Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities Aqueveque, Pablo Peña, Guisella Gutiérrez, Manuel Gómez, Britam Germany, Enrique Retamal, Gustavo Ortega-Bastidas, Paulina Sensors (Basel) Article In the search to enhance ergonomic risk assessments for upper limb work-related activities, this study introduced and validated the efficiency of an inertial motion capture system, paired with a specialized platform that digitalized the OCRA index. Conducted in a semi-controlled environment, the proposed methodology was compared to traditional risk classification techniques using both inertial and optical motion capture systems. The inertial method encompassed 18 units in a Bluetooth Low Energy tree topology network for activity recording, subsequently analyzed for risk using the platform. Principal outcomes emphasized the optical system’s preeminence, aligning closely with the conventional technique. The optical system’s superiority was further evident in its alignment with the traditional method. Meanwhile, the inertial system followed closely, with an error margin of just ±0.098 compared to the optical system. Risk classification was consistent across all systems. The inertial system demonstrated strong performance metrics, achieving F1-scores of 0.97 and 1 for “risk” and “no risk” classifications, respectively. Its distinct advantage of portability was reinforced by participants’ feedback on its user-friendliness. The results highlight the inertial system’s potential, mirroring the precision of both traditional and optical methods and achieving a 65% reduction in risk assessment time. This advancement mitigates the need for intricate video setups, emphasizing its potential in ergonomic assessments. MDPI 2023-09-02 /pmc/articles/PMC10490628/ /pubmed/37688078 http://dx.doi.org/10.3390/s23177623 Text en © 2023 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
Aqueveque, Pablo
Peña, Guisella
Gutiérrez, Manuel
Gómez, Britam
Germany, Enrique
Retamal, Gustavo
Ortega-Bastidas, Paulina
Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities
title Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities
title_full Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities
title_fullStr Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities
title_full_unstemmed Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities
title_short Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities
title_sort utilizing motion capture systems for instrumenting the ocra index: a study on risk classification for upper limb work-related activities
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490628/
https://www.ncbi.nlm.nih.gov/pubmed/37688078
http://dx.doi.org/10.3390/s23177623
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