EMG-Assisted Algorithm to Account for Shoulder Muscles Co-Contraction in Overhead Manual Handling

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Author(s)
Assila, Najoua
Pizzolato, Claudio
Martinez, Romain
Lloyd, David G
Begon, Mickael
Year published
2020
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Glenohumeral stability is essential for a healthy function of the shoulder. It is ensured partly by the scapulohumeral muscular balance. Accordingly, modelling muscle interactions is a key factor in the understanding of occupational pathologies, and the development of ergonomic interventions. While static optimization is commonly used to estimate muscle activations, it tends to underestimate the role of shoulder’s antagonist muscles. The purpose of this study was to implement experimental electromyographic (EMG) data to predict muscle activations that could account for the stabilizing role of the shoulder muscles. Kinematics ...
View more >Glenohumeral stability is essential for a healthy function of the shoulder. It is ensured partly by the scapulohumeral muscular balance. Accordingly, modelling muscle interactions is a key factor in the understanding of occupational pathologies, and the development of ergonomic interventions. While static optimization is commonly used to estimate muscle activations, it tends to underestimate the role of shoulder’s antagonist muscles. The purpose of this study was to implement experimental electromyographic (EMG) data to predict muscle activations that could account for the stabilizing role of the shoulder muscles. Kinematics and EMG were recorded from 36 participants while lifting a box from hip to eye level. Muscle activations and glenohumeral joint reactions were estimated using an EMG-assisted algorithm and compared to those obtained using static optimization with a generic and calibrated model. Muscle activations predicted with the EMG-assisted method were generally larger. Additionally, more interactions between the different rotator cuff muscles, as well as between primer actuators and stabilizers, were predicted with the EMG-assisted method. Finally, glenohumeral forces calculated from a calibrated model remained within the boundaries of the glenoid stability cone. These findings suggest that EMG-assisted methods could account for scapulohumeral muscle co-contraction, and thus their contribution to the glenohumeral stability. View Full-Text
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View more >Glenohumeral stability is essential for a healthy function of the shoulder. It is ensured partly by the scapulohumeral muscular balance. Accordingly, modelling muscle interactions is a key factor in the understanding of occupational pathologies, and the development of ergonomic interventions. While static optimization is commonly used to estimate muscle activations, it tends to underestimate the role of shoulder’s antagonist muscles. The purpose of this study was to implement experimental electromyographic (EMG) data to predict muscle activations that could account for the stabilizing role of the shoulder muscles. Kinematics and EMG were recorded from 36 participants while lifting a box from hip to eye level. Muscle activations and glenohumeral joint reactions were estimated using an EMG-assisted algorithm and compared to those obtained using static optimization with a generic and calibrated model. Muscle activations predicted with the EMG-assisted method were generally larger. Additionally, more interactions between the different rotator cuff muscles, as well as between primer actuators and stabilizers, were predicted with the EMG-assisted method. Finally, glenohumeral forces calculated from a calibrated model remained within the boundaries of the glenoid stability cone. These findings suggest that EMG-assisted methods could account for scapulohumeral muscle co-contraction, and thus their contribution to the glenohumeral stability. View Full-Text
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Journal Title
Applied Sciences
Volume
10
Issue
10
Copyright Statement
© 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/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Subject
Clinical sciences