{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:36:34Z","timestamp":1774485394862,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2014,5,30]],"date-time":"2014-05-30T00:00:00Z","timestamp":1401408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In this paper, we propose to use permutation entropy to explore whether the changes in electroencephalogram (EEG) data can effectively distinguish different phases in human absence epilepsy, i.e., the seizure-free, the pre-seizure and seizure phases. Permutation entropy is applied to analyze the EEG data from these three phases, each containing 100  19-channel EEG epochs of 2 s duration. The experimental results show the mean value of PE gradually decreases from the seizure-free to the seizure phase and provides evidence that these three different seizure phases in absence epilepsy can be effectively distinguished. Furthermore, our results strengthen the view that most frontal electrodes carry useful information and patterns that can help discriminate among different absence seizure phases.<\/jats:p>","DOI":"10.3390\/e16063049","type":"journal-article","created":{"date-parts":[[2014,5,30]],"date-time":"2014-05-30T12:00:34Z","timestamp":1401451234000},"page":"3049-3061","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":98,"title":["Using Permutation Entropy to Measure the Changes in EEG Signals During Absence Seizures"],"prefix":"10.3390","volume":"16","author":[{"given":"Jing","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning & IDG\/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China"},{"name":"Department of Electrical and Automatic Engineering, School of Information Engineering, Nanchang University, Nanchang 330031, China"}]},{"given":"Jiaqing","family":"Yan","sequence":"additional","affiliation":[{"name":"Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China"}]},{"given":"Xianzeng","family":"Liu","sequence":"additional","affiliation":[{"name":"The Comprehensive Epilepsy Center, Departments of Neurology and Neurosurgery,  Peking University People's Hospital, Beijing 100044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6390-626X","authenticated-orcid":false,"given":"Gaoxiang","family":"Ouyang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning & IDG\/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China"},{"name":"Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2014,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/S1474-4422(02)00003-0","article-title":"Prediction of epileptic seizures","volume":"1","author":"Litt","year":"2002","journal-title":"Lancet Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1046\/j.1528-1157.2001.10401.x","article-title":"A proposed diagnostic scheme for people with epileptic seizures and with epilepsy: Report of the ilae task force on classification and terminology","volume":"42","author":"Engel","year":"2001","journal-title":"Epilepsia"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.eplepsyres.2011.11.006","article-title":"Epileptic seizures from abnormal networks: Why some seizures defy predictability","volume":"99","author":"Anderson","year":"2012","journal-title":"Epilepsy Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1480","DOI":"10.1523\/JNEUROSCI.22-04-01480.2002","article-title":"Cortical focus drives widespread corticothalamic networks during spontaneous absence seizures in rats","volume":"22","author":"Meeren","year":"2002","journal-title":"J. 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