Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury

Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving s...

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Autores: Jordanic, Mislav|||0000-0001-6831-3327, Rojas Martínez, Mónica, Mañanas Villanueva, Miguel Ángel|||0000-0001-9836-6083, Alonso López, Joan Francesc|||0000-0002-2980-6716
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/100909
Acceso en línea:https://hdl.handle.net/2117/100909
https://dx.doi.org/10.1186/s12984-016-0151-8
Access Level:acceso abierto
Palabra clave:Spinal cord--Wounds and injuries
High-density electromyography
Myoelectric control
Pattern recognition
High density electromyography
Incomplete spinal cord injury
MYOELECTRIC PATTERN-RECOGNITION
BRAIN-COMPUTER INTERFACES
SURFACE EMG
CLASSIFICATION
RESTORATION
FEATURES
STROKE
MUSCLE
MAPS
Medul·la espinal--Ferides i lesions
Electromiografia
Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
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spelling Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injuryJordanic, Mislav|||0000-0001-6831-3327Rojas Martínez, MónicaMañanas Villanueva, Miguel Ángel|||0000-0001-9836-6083Alonso López, Joan Francesc|||0000-0002-2980-6716Spinal cord--Wounds and injuriesHigh-density electromyographyMyoelectric controlPattern recognitionHigh density electromyographyIncomplete spinal cord injuryMYOELECTRIC PATTERN-RECOGNITIONBRAIN-COMPUTER INTERFACESSURFACE EMGCLASSIFICATIONRESTORATIONFEATURESSTROKEMUSCLEMAPSMedul·la espinal--Ferides i lesionsElectromiografiaÀrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdicaBackground: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.Peer Reviewed20162016-04-2920172017-02-13journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/100909https://dx.doi.org/10.1186/s12984-016-0151-827129309reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1009092026-05-27T15:37:01Z
dc.title.none.fl_str_mv Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
title Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
spellingShingle Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
Jordanic, Mislav|||0000-0001-6831-3327
Spinal cord--Wounds and injuries
High-density electromyography
Myoelectric control
Pattern recognition
High density electromyography
Incomplete spinal cord injury
MYOELECTRIC PATTERN-RECOGNITION
BRAIN-COMPUTER INTERFACES
SURFACE EMG
CLASSIFICATION
RESTORATION
FEATURES
STROKE
MUSCLE
MAPS
Medul·la espinal--Ferides i lesions
Electromiografia
Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
title_short Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
title_full Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
title_fullStr Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
title_full_unstemmed Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
title_sort Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
dc.creator.none.fl_str_mv Jordanic, Mislav|||0000-0001-6831-3327
Rojas Martínez, Mónica
Mañanas Villanueva, Miguel Ángel|||0000-0001-9836-6083
Alonso López, Joan Francesc|||0000-0002-2980-6716
author Jordanic, Mislav|||0000-0001-6831-3327
author_facet Jordanic, Mislav|||0000-0001-6831-3327
Rojas Martínez, Mónica
Mañanas Villanueva, Miguel Ángel|||0000-0001-9836-6083
Alonso López, Joan Francesc|||0000-0002-2980-6716
author_role author
author2 Rojas Martínez, Mónica
Mañanas Villanueva, Miguel Ángel|||0000-0001-9836-6083
Alonso López, Joan Francesc|||0000-0002-2980-6716
author2_role author
author
author
dc.subject.none.fl_str_mv Spinal cord--Wounds and injuries
High-density electromyography
Myoelectric control
Pattern recognition
High density electromyography
Incomplete spinal cord injury
MYOELECTRIC PATTERN-RECOGNITION
BRAIN-COMPUTER INTERFACES
SURFACE EMG
CLASSIFICATION
RESTORATION
FEATURES
STROKE
MUSCLE
MAPS
Medul·la espinal--Ferides i lesions
Electromiografia
Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
topic Spinal cord--Wounds and injuries
High-density electromyography
Myoelectric control
Pattern recognition
High density electromyography
Incomplete spinal cord injury
MYOELECTRIC PATTERN-RECOGNITION
BRAIN-COMPUTER INTERFACES
SURFACE EMG
CLASSIFICATION
RESTORATION
FEATURES
STROKE
MUSCLE
MAPS
Medul·la espinal--Ferides i lesions
Electromiografia
Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
description Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-04-29
2017
2017-02-13
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/100909
https://dx.doi.org/10.1186/s12984-016-0151-8
27129309
url https://hdl.handle.net/2117/100909
https://dx.doi.org/10.1186/s12984-016-0151-8
identifier_str_mv 27129309
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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