Cargando…

Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine

Low back pain (LBP), the leading cause of disability worldwide, remains one of the most common and challenging problems in occupational musculoskeletal disorders. The effective assessment of LBP injury risk, and the design of appropriate treatment modalities and rehabilitation protocols, require acc...

Descripción completa

Detalles Bibliográficos
Autores principales: Sharifzadeh-Kermani, Alireza, Arjmand, Navid, Vossoughi, Gholamreza, Shirazi-Adl, Aboulfazl, Patwardhan, Avinash G., Parnianpour, Mohamad, Khalaf, Kinda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431630/
https://www.ncbi.nlm.nih.gov/pubmed/32850767
http://dx.doi.org/10.3389/fbioe.2020.00949
_version_ 1783571623643709440
author Sharifzadeh-Kermani, Alireza
Arjmand, Navid
Vossoughi, Gholamreza
Shirazi-Adl, Aboulfazl
Patwardhan, Avinash G.
Parnianpour, Mohamad
Khalaf, Kinda
author_facet Sharifzadeh-Kermani, Alireza
Arjmand, Navid
Vossoughi, Gholamreza
Shirazi-Adl, Aboulfazl
Patwardhan, Avinash G.
Parnianpour, Mohamad
Khalaf, Kinda
author_sort Sharifzadeh-Kermani, Alireza
collection PubMed
description Low back pain (LBP), the leading cause of disability worldwide, remains one of the most common and challenging problems in occupational musculoskeletal disorders. The effective assessment of LBP injury risk, and the design of appropriate treatment modalities and rehabilitation protocols, require accurate estimation of the mechanical spinal loads during different activities. This study aimed to: (1) develop a novel 2D beam-column finite element control-based model of the lumbar spine and compare its predictions for muscle forces and spinal loads to those resulting from a geometrically matched equilibrium-based model; (2) test, using the foregoing control-based finite element model, the validity of the follower load (FL) concept suggested in the geometrically matched model; and (3) investigate the effect of change in the magnitude of the external load on trunk muscle activation patterns. A simple 2D continuous beam-column model of the human lumbar spine, incorporating five pairs of Hill’s muscle models, was developed in the frontal plane. Bio-inspired fuzzy neuro-controllers were used to maintain a laterally bent posture under five different external loading conditions. Muscle forces were assigned based on minimizing the kinematic error between target and actual postures, while imposing a penalty on muscular activation levels. As compared to the geometrically matched model, our control-based model predicted similar patterns for muscle forces, but at considerably lower values. Moreover, irrespective of the external loading conditions, a near (<3°) optimal FL on the spine was generated by the control-based predicted muscle forces. The variation of the muscle forces with the magnitude of the external load within the simulated range at the L1 level was found linear. This work presents a novel methodology, based on a bio-inspired control strategy, that can be used to estimate trunk muscle forces for various clinical and occupational applications toward shedding light on the ever-elusive LBP etiology.
format Online
Article
Text
id pubmed-7431630
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-74316302020-08-25 Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine Sharifzadeh-Kermani, Alireza Arjmand, Navid Vossoughi, Gholamreza Shirazi-Adl, Aboulfazl Patwardhan, Avinash G. Parnianpour, Mohamad Khalaf, Kinda Front Bioeng Biotechnol Bioengineering and Biotechnology Low back pain (LBP), the leading cause of disability worldwide, remains one of the most common and challenging problems in occupational musculoskeletal disorders. The effective assessment of LBP injury risk, and the design of appropriate treatment modalities and rehabilitation protocols, require accurate estimation of the mechanical spinal loads during different activities. This study aimed to: (1) develop a novel 2D beam-column finite element control-based model of the lumbar spine and compare its predictions for muscle forces and spinal loads to those resulting from a geometrically matched equilibrium-based model; (2) test, using the foregoing control-based finite element model, the validity of the follower load (FL) concept suggested in the geometrically matched model; and (3) investigate the effect of change in the magnitude of the external load on trunk muscle activation patterns. A simple 2D continuous beam-column model of the human lumbar spine, incorporating five pairs of Hill’s muscle models, was developed in the frontal plane. Bio-inspired fuzzy neuro-controllers were used to maintain a laterally bent posture under five different external loading conditions. Muscle forces were assigned based on minimizing the kinematic error between target and actual postures, while imposing a penalty on muscular activation levels. As compared to the geometrically matched model, our control-based model predicted similar patterns for muscle forces, but at considerably lower values. Moreover, irrespective of the external loading conditions, a near (<3°) optimal FL on the spine was generated by the control-based predicted muscle forces. The variation of the muscle forces with the magnitude of the external load within the simulated range at the L1 level was found linear. This work presents a novel methodology, based on a bio-inspired control strategy, that can be used to estimate trunk muscle forces for various clinical and occupational applications toward shedding light on the ever-elusive LBP etiology. Frontiers Media S.A. 2020-08-11 /pmc/articles/PMC7431630/ /pubmed/32850767 http://dx.doi.org/10.3389/fbioe.2020.00949 Text en Copyright © 2020 Sharifzadeh-Kermani, Arjmand, Vossoughi, Shirazi-Adl, Patwardhan, Parnianpour and Khalaf. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Sharifzadeh-Kermani, Alireza
Arjmand, Navid
Vossoughi, Gholamreza
Shirazi-Adl, Aboulfazl
Patwardhan, Avinash G.
Parnianpour, Mohamad
Khalaf, Kinda
Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine
title Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine
title_full Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine
title_fullStr Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine
title_full_unstemmed Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine
title_short Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine
title_sort estimation of trunk muscle forces using a bio-inspired control strategy implemented in a neuro-osteo-ligamentous finite element model of the lumbar spine
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431630/
https://www.ncbi.nlm.nih.gov/pubmed/32850767
http://dx.doi.org/10.3389/fbioe.2020.00949
work_keys_str_mv AT sharifzadehkermanialireza estimationoftrunkmuscleforcesusingabioinspiredcontrolstrategyimplementedinaneuroosteoligamentousfiniteelementmodelofthelumbarspine
AT arjmandnavid estimationoftrunkmuscleforcesusingabioinspiredcontrolstrategyimplementedinaneuroosteoligamentousfiniteelementmodelofthelumbarspine
AT vossoughigholamreza estimationoftrunkmuscleforcesusingabioinspiredcontrolstrategyimplementedinaneuroosteoligamentousfiniteelementmodelofthelumbarspine
AT shiraziadlaboulfazl estimationoftrunkmuscleforcesusingabioinspiredcontrolstrategyimplementedinaneuroosteoligamentousfiniteelementmodelofthelumbarspine
AT patwardhanavinashg estimationoftrunkmuscleforcesusingabioinspiredcontrolstrategyimplementedinaneuroosteoligamentousfiniteelementmodelofthelumbarspine
AT parnianpourmohamad estimationoftrunkmuscleforcesusingabioinspiredcontrolstrategyimplementedinaneuroosteoligamentousfiniteelementmodelofthelumbarspine
AT khalafkinda estimationoftrunkmuscleforcesusingabioinspiredcontrolstrategyimplementedinaneuroosteoligamentousfiniteelementmodelofthelumbarspine