{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T09:19:33Z","timestamp":1778404773811,"version":"3.51.4"},"reference-count":81,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2017,8,21]],"date-time":"2017-08-21T00:00:00Z","timestamp":1503273600000},"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>Electroencephalography (EEG) is frequently used in functional neurological assessment of children with neurological and neuropsychiatric disorders. Multiscale entropy (MSE) can reveal complexity in both short and long time scales and is more feasible in the analysis of EEG. Entropy-based estimation of EEG complexity is a powerful tool in investigating the underlying disturbances of neural networks of the brain. Most neurological and neuropsychiatric disorders in childhood affect the early stage of brain development. The analysis of EEG complexity may show the influences of different neurological and neuropsychiatric disorders on different regions of the brain during development. This article aims to give a brief summary of current concepts of MSE analysis in pediatric neurological and neuropsychiatric disorders. Studies utilizing MSE or its modifications for investigating neurological and neuropsychiatric disorders in children were reviewed. Abnormal EEG complexity was shown in a variety of childhood neurological and neuropsychiatric diseases, including autism, attention deficit\/hyperactivity disorder, Tourette syndrome, and epilepsy in infancy and childhood. MSE has been shown to be a powerful method for analyzing the non-linear anomaly of EEG in childhood neurological diseases. Further studies are needed to show its clinical implications on diagnosis, treatment, and outcome prediction.<\/jats:p>","DOI":"10.3390\/e19080428","type":"journal-article","created":{"date-parts":[[2017,8,21]],"date-time":"2017-08-21T11:10:51Z","timestamp":1503313851000},"page":"428","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["The Potential Application of Multiscale Entropy Analysis of Electroencephalography in Children with Neurological and Neuropsychiatric Disorders"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3692-1018","authenticated-orcid":false,"given":"Yen-Ju","family":"Chu","sequence":"first","affiliation":[{"name":"Department of Pediatric Neurology, National Taiwan University Children\u2019s Hospital, Taipei 100, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chi-Feng","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiann-Shing","family":"Shieh","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan"},{"name":"Innovation Center for Biomedical and Healthcare Technology, Yuan Ze University, Taoyuan 32003, Taiwan"},{"name":"Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan 32003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wang-Tso","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Pediatric Neurology, National Taiwan University Children\u2019s Hospital, Taipei 100, Taiwan"},{"name":"Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei 10617, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1126\/science.1173299","article-title":"Scale-free networks: A decade and beyond","volume":"325","author":"Barabasi","year":"2009","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1016\/j.clinph.2012.01.011","article-title":"The organization of physiological brain networks","volume":"123","author":"Stam","year":"2012","journal-title":"Clin. 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