Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input
Coordinated activation of muscles is the basis for human locomotion. Impaired muscular activation is related to poor movement performance and disability. To restore movement performance, information about the subject's individual muscular activation is of high relevance. Surface electromyograph...
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Frontiers Media S.A.
2020-12-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2020.603550/full |
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doaj-9efeeacdd60f43ae97fe24b051e826822020-12-08T08:36:18ZengFrontiers Media S.A.Frontiers in Neurology1664-22952020-12-011110.3389/fneur.2020.603550603550Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical InputCatherine Disselhorst-KlugSybele WilliamsCoordinated activation of muscles is the basis for human locomotion. Impaired muscular activation is related to poor movement performance and disability. To restore movement performance, information about the subject's individual muscular activation is of high relevance. Surface electromyography (sEMG) allows the pain-free assessment of muscular activation and many ready-to-use technologies are available. They enable the usage of sEMG measurements in several applications. However, due to the fact that in most rehabilitation applications dynamic conditions are analyzed, the correct interpretation of sEMG signals remains difficult which hinders the spread of sEMG in clinical applications. From biomechanics it is well-known that the sEMG signal depends on muscle fiber length, contraction velocity, contraction type and on the muscle's biomechanical moment. In non-isometric conditions these biomechanical factors have to be considered when analyzing sEMG signals. Additionally, the central nervous system control strategies used to activate synergistic and antagonistic muscles have to be taken into consideration. These central nervous system activation strategies are rarely known in physiology and are hard to manage in pathology. In this perspective report we discuss how the consideration of biomechanical factors leads to more reliable information extraction from sEMG signals and how the limitations of sEMG can be overcome in dynamic conditions. This is a prerequisite if the use of sEMG in rehabilitation applications is to extend. Examples will be given showing how the integration of biomechanical knowledge into the interpretation of sEMG helps to identify the central nervous system activation strategies involved and leads to relevant clinical information.https://www.frontiersin.org/articles/10.3389/fneur.2020.603550/fullsurface electromyographybiomechanicsneuromechanicsclinical applicationrehabilitation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Catherine Disselhorst-Klug Sybele Williams |
spellingShingle |
Catherine Disselhorst-Klug Sybele Williams Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input Frontiers in Neurology surface electromyography biomechanics neuromechanics clinical application rehabilitation |
author_facet |
Catherine Disselhorst-Klug Sybele Williams |
author_sort |
Catherine Disselhorst-Klug |
title |
Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input |
title_short |
Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input |
title_full |
Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input |
title_fullStr |
Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input |
title_full_unstemmed |
Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input |
title_sort |
surface electromyography meets biomechanics: correct interpretation of semg-signals in neuro-rehabilitation needs biomechanical input |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neurology |
issn |
1664-2295 |
publishDate |
2020-12-01 |
description |
Coordinated activation of muscles is the basis for human locomotion. Impaired muscular activation is related to poor movement performance and disability. To restore movement performance, information about the subject's individual muscular activation is of high relevance. Surface electromyography (sEMG) allows the pain-free assessment of muscular activation and many ready-to-use technologies are available. They enable the usage of sEMG measurements in several applications. However, due to the fact that in most rehabilitation applications dynamic conditions are analyzed, the correct interpretation of sEMG signals remains difficult which hinders the spread of sEMG in clinical applications. From biomechanics it is well-known that the sEMG signal depends on muscle fiber length, contraction velocity, contraction type and on the muscle's biomechanical moment. In non-isometric conditions these biomechanical factors have to be considered when analyzing sEMG signals. Additionally, the central nervous system control strategies used to activate synergistic and antagonistic muscles have to be taken into consideration. These central nervous system activation strategies are rarely known in physiology and are hard to manage in pathology. In this perspective report we discuss how the consideration of biomechanical factors leads to more reliable information extraction from sEMG signals and how the limitations of sEMG can be overcome in dynamic conditions. This is a prerequisite if the use of sEMG in rehabilitation applications is to extend. Examples will be given showing how the integration of biomechanical knowledge into the interpretation of sEMG helps to identify the central nervous system activation strategies involved and leads to relevant clinical information. |
topic |
surface electromyography biomechanics neuromechanics clinical application rehabilitation |
url |
https://www.frontiersin.org/articles/10.3389/fneur.2020.603550/full |
work_keys_str_mv |
AT catherinedisselhorstklug surfaceelectromyographymeetsbiomechanicscorrectinterpretationofsemgsignalsinneurorehabilitationneedsbiomechanicalinput AT sybelewilliams surfaceelectromyographymeetsbiomechanicscorrectinterpretationofsemgsignalsinneurorehabilitationneedsbiomechanicalinput |
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