{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T06:39:00Z","timestamp":1778654340918,"version":"3.51.4"},"reference-count":44,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,5,16]],"date-time":"2016-05-16T00:00:00Z","timestamp":1463356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Biomedical 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\u2019s disease. Interestingly, about 50%\u201370% of the cases of ET have a genetic origin. One of the most used standard tests for clinical diagnosis of ET is Archimedes\u2019 spiral drawing. This work focuses on the selection of non-linear biomarkers from such drawings and handwriting, and it is part of a wider cross study on the diagnosis of essential tremor, where our piece of research presents the selection of entropy features for early ET diagnosis. Classic entropy features are compared with features based on permutation entropy. Automatic analysis system settled on several Machine Learning paradigms is performed, while automatic features selection is implemented by means of ANOVA (analysis of variance) test. The obtained results for early detection are promising and appear applicable to real environments.<\/jats:p>","DOI":"10.3390\/e18050184","type":"journal-article","created":{"date-parts":[[2016,5,17]],"date-time":"2016-05-17T10:20:11Z","timestamp":1463480411000},"page":"184","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Selection of Entropy Based Features for Automatic Analysis of Essential Tremor"],"prefix":"10.3390","volume":"18","author":[{"given":"Karmele","family":"L\u00f3pez-de-Ipi\u00f1a","sequence":"first","affiliation":[{"name":"Systems Engineering and Automation Department, University of the Basque Country UPV\/EHU, Donostia 20018 , Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6534-1979","authenticated-orcid":false,"given":"Jordi","family":"Sol\u00e9-Casals","sequence":"additional","affiliation":[{"name":"Data and Signal Processing Research Group, University of Vic\u2014Central University of Catalonia, Vic, Catalonia 08500, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0605-1282","authenticated-orcid":false,"given":"Marcos","family":"Faundez-Zanuy","sequence":"additional","affiliation":[{"name":"Escola Superior Polit\u00e8cnica Tecnocampus (UPF), Matar\u00f3, Catalonia 08302, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pilar","family":"Calvo","sequence":"additional","affiliation":[{"name":"Systems Engineering and Automation Department, University of the Basque Country UPV\/EHU, Donostia 20018 , Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enric","family":"Sesa","sequence":"additional","affiliation":[{"name":"Escola Superior Polit\u00e8cnica Tecnocampus (UPF), Matar\u00f3, Catalonia 08302, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Unai","family":"Martinez de Lizarduy","sequence":"additional","affiliation":[{"name":"Systems Engineering and Automation Department, University of the Basque Country UPV\/EHU, Donostia 20018 , Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patricia","family":"De La Riva","sequence":"additional","affiliation":[{"name":"BioDonostia Health Institute, Neurology Department Hospital Donostia, Donostia 20014, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose","family":"Marti-Masso","sequence":"additional","affiliation":[{"name":"BioDonostia Health Institute, Neurology Department Hospital Donostia, Donostia 20014, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Blanca","family":"Beitia","sequence":"additional","affiliation":[{"name":"Systems Engineering and Automation Department, University of the Basque Country UPV\/EHU, Donostia 20018 , Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alberto","family":"Bergareche","sequence":"additional","affiliation":[{"name":"BioDonostia Health Institute, Neurology Department Hospital Donostia, Donostia 20014, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,5,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1553","DOI":"10.3390\/e14081553","article-title":"Permutation entropy and its main biomedical and econophysics applications: A review","volume":"14","author":"Zanin","year":"2012","journal-title":"Entropy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.3390\/e14071186","article-title":"Multivariate Multi-Scale Permutation Entropy for Complexiy Analysis of Alzheimer\u2019s Disease EEG","volume":"14","author":"Morabito","year":"2012","journal-title":"Entropy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6133","DOI":"10.3390\/e16116133","article-title":"Application of, Entropy and Fractal Dimension Analyses to the Pattern Recognition of Contaminated Fish Responses in Aquaculture","volume":"16","author":"Eguiraun","year":"2014","journal-title":"Entropy"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Costa, M., Goldberger, A., and Peng, C.K. 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