{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T04:25:55Z","timestamp":1769315155767,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2017,2,16]],"date-time":"2017-02-16T00:00:00Z","timestamp":1487203200000},"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>In this contribution, a comparison between different permutation entropies as classifiers of electroencephalogram (EEG) records corresponding to normal and pre-ictal states is made. A discrete probability distribution function derived from symbolization techniques applied to the EEG signal is used to calculate the Tsallis entropy, Shannon Entropy, Renyi Entropy, and Min Entropy, and they are used separately as the only independent variable in a logistic regression model in order to evaluate its capacity as a classification variable in a inferential manner. The area under the Receiver Operating Characteristic (ROC) curve, along with the accuracy, sensitivity, and specificity are used to compare the models. All the permutation entropies are excellent classifiers, with an accuracy greater than 94.5% in every case, and a sensitivity greater than 97%. Accounting for the amplitude in the symbolization technique retains more information of the signal than its counterparts, and it could be a good candidate for automatic classification of EEG signals.<\/jats:p>","DOI":"10.3390\/e19020072","type":"journal-article","created":{"date-parts":[[2017,2,16]],"date-time":"2017-02-16T12:55:34Z","timestamp":1487249734000},"page":"72","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Classification of Normal and Pre-Ictal EEG Signals Using Permutation Entropies and a Generalized Linear Model as a Classifier"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6945-2916","authenticated-orcid":false,"given":"Francisco","family":"Redelico","sequence":"first","affiliation":[{"name":"Departamento de Inform\u00e1tica en Salud, Hospital Italiano de Buenos Aires, C1199ABB Ciudad Aut\u00f3noma de Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco","family":"Traversaro","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico de Buenos Aires (ITBA), C1106ACD Ciudad Aut\u00f3noma de Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda","family":"Garc\u00eda","sequence":"additional","affiliation":[{"name":"Servicio de Neurolog\u00eda, Hospital Italiano de Buenos Aires, Gral. Juan Domingo Per\u00f3n 4190, C1199ABB Ciudad Aut\u00f3noma de Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Walter","family":"Silva","sequence":"additional","affiliation":[{"name":"Servicio de Neurologia Infantil\u2014Instituto Universitario (IUHI)\u2014Hospital Italiano de Buenos Aires, Tte. Gral. Juan Domingo Per\u00f3n 4190, C1199ABB Ciudad Aut\u00f3noma de Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1288-2528","authenticated-orcid":false,"given":"Osvaldo","family":"Rosso","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica en Salud, Hospital Italiano de Buenos Aires, C1199ABB Ciudad Aut\u00f3noma de Buenos Aires, Argentina"},{"name":"Instituto de F\u00edsica, Universidade Federal de Alagoas (UFAL), 57072-900 Macei\u00f3, Brazil"},{"name":"Complex Systems Group, Facultad de Ingenier\u00eda y Ciencias Aplicadas, Universidad de los Andes, 12455 Santiago, Chile"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcelo","family":"Risk","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica en Salud, Hospital Italiano de Buenos Aires, C1199ABB Ciudad Aut\u00f3noma de Buenos Aires, Argentina"},{"name":"Instituto Tecnol\u00f3gico de Buenos Aires (ITBA), C1106ACD Ciudad Aut\u00f3noma de Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1111\/j.0013-9580.2005.66104.x","article-title":"Epileptic seizures and epilepsy: Definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE)","volume":"46","author":"Fisher","year":"2005","journal-title":"Epilepsia"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1111\/epi.12550","article-title":"ILAE official report: A practical clinical definition of epilepsy","volume":"55","author":"Fisher","year":"2014","journal-title":"Epilepsia"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"174102","DOI":"10.1103\/PhysRevLett.88.174102","article-title":"Permutation entropy: A natural complexity measure for time series","volume":"88","author":"Bandt","year":"2002","journal-title":"Phys. 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