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dc.contributor.authorJordanic, Mislav
dc.contributor.authorRojas Martínez, Mónica
dc.contributor.authorMañanas Villanueva, Miguel Ángel
dc.contributor.authorAlonso López, Joan Francesc
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2017-02-13T11:51:44Z
dc.date.available2017-02-13T11:51:44Z
dc.date.issued2016-04-29
dc.identifier.citationJordanic, M., Rojas, M., Mañanas, M.A., Alonso, J.F. Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury. "Journal of neuroengineering and rehabilitation", 29 Abril 2016, vol. 13, p. 1-11.
dc.identifier.issn1743-0003
dc.identifier.urihttp://hdl.handle.net/2117/100909
dc.description.abstractBackground: 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.
dc.format.extent11 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
dc.subject.lcshSpinal cord--Wounds and injuries
dc.subject.lcshHigh-density electromyography
dc.subject.otherMyoelectric control
dc.subject.otherPattern recognition
dc.subject.otherHigh density electromyography
dc.subject.otherIncomplete spinal cord injury
dc.subject.otherMYOELECTRIC PATTERN-RECOGNITION
dc.subject.otherBRAIN-COMPUTER INTERFACES
dc.subject.otherSURFACE EMG
dc.subject.otherCLASSIFICATION
dc.subject.otherRESTORATION
dc.subject.otherFEATURES
dc.subject.otherSTROKE
dc.subject.otherMUSCLE
dc.subject.otherMAPS
dc.titleSpatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
dc.typeArticle
dc.subject.lemacMedul·la espinal--Ferides i lesions
dc.subject.lemacElectromiografia
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy
dc.identifier.doi10.1186/s12984-016-0151-8
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-016-0151-8
dc.rights.accessOpen Access
local.identifier.drac18736368
dc.description.versionPostprint (published version)
local.citation.authorJordanic, M.; Rojas, M.; Mañanas, M.A.; Alonso, J.F.
local.citation.publicationNameJournal of neuroengineering and rehabilitation
local.citation.volume13
local.citation.startingPage1
local.citation.endingPage11
dc.identifier.pmid27129309


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