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dc.contributor.authorUrra, Oiane
dc.contributor.authorCasals Gelpí, Alicia
dc.contributor.authorJané Campos, Raimon
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherInstitut de Bioenginyeria de Catalunya
dc.date.accessioned2015-05-25T13:36:09Z
dc.date.available2015-12-31T01:31:04Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationUrra, O.; Casals, A.; Jane, R. Evaluating spatial characteristics of upper-limb movements from EMG signals. A: "XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013: MEDICON 2013, 25-28 September 2013, Seville, Spain". Springer, 2014, p. 1795-1798.
dc.identifier.isbn978-3-319-00845-5
dc.identifier.urihttp://hdl.handle.net/2117/28032
dc.description.abstractStroke is a major cause of disability, usually causing hemiplegic damage on the motor abilities of the patient. Stroke rehabilitation seeks restoring normal motion on the affected limb. However, ‘normality’ of movements is usually assessed by clinical and functional tests, without considering how the motor system responds to therapy. We hypothesized that electromyographic (EMG) recordings could provide useful information for evaluating the outcome of rehabilitation from a neuromuscular perspective. Four healthy subjects were asked to perform 14 different functional movements simulating the action of reaching over a table. Each movement was defined according to the starting and target positions that the subject had to connect using linear trajectories. Bipolar recordings of EMG signals were taken from biceps and triceps muscles, and spectral and temporal characteristics were extracted for each movement. Using pattern recognition techniques we found that only two EMG channels were sufficient to accurately determine the spatial characteristics of motor activity: movement direction, length and execution zone. Our results suggest that muscles may fire in a patterned way depending on the specific characteristics of the movement and that EMG signals may codify such detailed information. These findings may be of great value to quantitatively assess poststroke rehabilitation and to compare the neuromuscular activity of the affected and unaffected limbs, from a physiological perspective. Furthermore, disturbed movements could be characterized in terms of the muscle function to identify, which is the spatial characteristic that fails, e.g. movement direction, and guide personalized rehabilitation to enhance the training of such characteristic.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes
dc.subject.lcshNeuromuscular diseases
dc.subject.otherEMG
dc.subject.otherMovement spatial characteristics
dc.subject.otherPattern recognition
dc.subject.otherStroke rehabilitation
dc.subject.otherUpper-limb
dc.titleEvaluating spatial characteristics of upper-limb movements from EMG signals
dc.typePart of book or chapter of book
dc.subject.lemacMalaties neuromusculars
dc.contributor.groupUniversitat Politècnica de Catalunya. GRINS - Grup de Recerca en Robòtica Intel·ligent i Sistemes
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation
dc.identifier.doi10.1007/978-3-319-00846-2
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.springer.com/de/book/9783319008455
dc.rights.accessOpen Access
local.identifier.drac15592829
dc.description.versionPostprint (author’s final draft)
local.citation.authorUrra, O.; Casals, A.; Jane, R.
local.citation.publicationNameXIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013: MEDICON 2013, 25-28 September 2013, Seville, Spain
local.citation.startingPage1795
local.citation.endingPage1798


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