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dc.contributor.authorLópez-de-Ipiña, Karmele
dc.contributor.authorSolé-Casals, Jordi
dc.contributor.authorFaundez-Zanuy, Marcos
dc.contributor.authorCalvo, Pilar Maria
dc.contributor.authorSesa-Nogueras, Enric
dc.contributor.authorMartinez de lizarduy, Unai
dc.contributor.authorRiva de la, Patricia
dc.contributor.authorMarti Masso, Jose Felix
dc.contributor.authorBeitia, Blanca
dc.contributor.authorBergareche, Alberto
dc.date.accessioned2023-12-07T13:46:49Z
dc.date.available2023-12-07T13:46:49Z
dc.date.issued2016
dc.identifier.citationLópez-de-Ipiña K, Solé-Casals J, Faundez-Zanuy M, Calvo PM, Sesa E, Martinez de Lizarduy U, De La Riva P, Marti-Masso JF, Beitia B, Bergareche A. Selection of Entropy Based Features for Automatic Analysis of Essential Tremor. Entropy. 2016;18(5):184. DOI: 10.3390/e18050184ca
dc.identifier.issn1099-4300ca
dc.identifier.urihttp://hdl.handle.net/20.500.12367/2535
dc.description.abstractBiomedical systems produce biosignals that arise from interaction mechanisms. In a general form, those mechanisms occur across multiple scales, both spatial and temporal, and contain linear and non-linear information. In this framework, entropy measures are good candidates in order provide useful evidence about disorder in the system, lack of information in time-series and/or irregularity of the signals. The most common movement disorder is essential tremor (ET), which occurs 20 times more than Parkinson’s disease. Interestingly, about 50%–70% of the cases of ET have a genetic origin. One of the most used standard tests for clinical diagnosis of ET is Archimedes’ spiral drawing. [...]ca
dc.format.extent22 p.ca
dc.language.isoengca
dc.publisherMDPIca
dc.relation.ispartofEntropy. 2016;18(5):184ca
dc.rights© 2016 by the authors; licensee MDPI, Basel, Switzerland.ca
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.otherPermutation entropyca
dc.subject.otherEssential tremorca
dc.subject.otherAutomatic drawing analysisca
dc.subject.otherArchimedes’ spiralca
dc.subject.otherNon-linear featuresca
dc.subject.otherAutomatic feature selectionca
dc.titleSelection of entropy based features for automatic analysis of essential tremorca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/publishedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapca
dc.identifier.doi10.3390/e18050184ca


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© 2016 by the authors; licensee MDPI, Basel, Switzerland.
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/
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