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Article: Network modeling and analysis of lumbar muscle surface EMG signals during flexion-extension in individuals with and without low back pain

TitleNetwork modeling and analysis of lumbar muscle surface EMG signals during flexion-extension in individuals with and without low back pain
Authors
Issue Date2011
PublisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/locate/jelekin
Citation
Journal Of Electromyography And Kinesiology, 2011, v. 21 n. 6, p. 913-921 How to Cite?
AbstractIn this paper, we propose modeling the activity coordination network between lumbar muscles using surface electromyography (sEMG) signals and performing the network analysis to compare the lumbar muscle coordination patterns between patients with low back pain (LBP) and healthy control subjects. Ten healthy subjects and eleven LBP patients were asked to perform flexion-extension task, and the sEMG signals were recorded. Both the subject-level and the group-level PC fdr algorithms are applied to learn the sEMG coordination networks with the error-rate being controlled. The network features are further characterized in terms of network symmetry, global efficiency, clustering coefficient and graph modules. The results indicate that the networks representing the normal group are much closer to the order networks and clearly exhibit globally symmetric patterns between the left and right sEMG channels. While the coordination activities between sEMG channels for the patient group are more likely to cluster locally and the group network shows the loss of global symmetric patterns. As a complementary tool to the physical and anatomical analysis, the proposed network analysis approach allows the visualization of the muscle coordination activities and the extraction of more informative features from the sEMG data for low back pain studies. © 2011 Elsevier Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/159741
ISSN
2015 Impact Factor: 1.53
2015 SCImago Journal Rankings: 0.886
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLiu, Aen_HK
dc.contributor.authorWang, ZJen_HK
dc.contributor.authorHu, Yen_HK
dc.date.accessioned2012-08-16T05:55:26Z-
dc.date.available2012-08-16T05:55:26Z-
dc.date.issued2011en_HK
dc.identifier.citationJournal Of Electromyography And Kinesiology, 2011, v. 21 n. 6, p. 913-921en_HK
dc.identifier.issn1050-6411en_HK
dc.identifier.urihttp://hdl.handle.net/10722/159741-
dc.description.abstractIn this paper, we propose modeling the activity coordination network between lumbar muscles using surface electromyography (sEMG) signals and performing the network analysis to compare the lumbar muscle coordination patterns between patients with low back pain (LBP) and healthy control subjects. Ten healthy subjects and eleven LBP patients were asked to perform flexion-extension task, and the sEMG signals were recorded. Both the subject-level and the group-level PC fdr algorithms are applied to learn the sEMG coordination networks with the error-rate being controlled. The network features are further characterized in terms of network symmetry, global efficiency, clustering coefficient and graph modules. The results indicate that the networks representing the normal group are much closer to the order networks and clearly exhibit globally symmetric patterns between the left and right sEMG channels. While the coordination activities between sEMG channels for the patient group are more likely to cluster locally and the group network shows the loss of global symmetric patterns. As a complementary tool to the physical and anatomical analysis, the proposed network analysis approach allows the visualization of the muscle coordination activities and the extraction of more informative features from the sEMG data for low back pain studies. © 2011 Elsevier Ltd.en_HK
dc.languageengen_US
dc.publisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/locate/jelekinen_HK
dc.relation.ispartofJournal of Electromyography and Kinesiologyen_HK
dc.subject.meshAdulten_HK
dc.subject.meshComputer Simulationen_HK
dc.subject.meshElectromyography - methodsen_HK
dc.subject.meshHumansen_HK
dc.subject.meshLow Back Pain - physiopathologyen_HK
dc.subject.meshLumbar Vertebrae - physiopathologyen_HK
dc.subject.meshMaleen_HK
dc.subject.meshModels, Neurologicalen_HK
dc.subject.meshMovementen_HK
dc.subject.meshMuscle Contractionen_HK
dc.subject.meshMuscle, Skeletal - physiopathologyen_HK
dc.subject.meshRange of Motion, Articularen_HK
dc.titleNetwork modeling and analysis of lumbar muscle surface EMG signals during flexion-extension in individuals with and without low back painen_HK
dc.typeArticleen_HK
dc.identifier.emailHu, Y:yhud@hku.hken_HK
dc.identifier.authorityHu, Y=rp00432en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jelekin.2011.08.012en_HK
dc.identifier.pmid21943775-
dc.identifier.scopuseid_2-s2.0-80054979821en_HK
dc.identifier.hkuros202314en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80054979821&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume21en_HK
dc.identifier.issue6en_HK
dc.identifier.spage913en_HK
dc.identifier.epage921en_HK
dc.identifier.isiWOS:000296573900005-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLiu, A=54397386900en_HK
dc.identifier.scopusauthoridWang, ZJ=35294001800en_HK
dc.identifier.scopusauthoridHu, Y=7407116091en_HK
dc.identifier.citeulike9833936-

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