{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T07:54:33Z","timestamp":1769759673920,"version":"3.49.0"},"reference-count":43,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2023,4,16]],"date-time":"2023-04-16T00:00:00Z","timestamp":1681603200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003196","name":"Ministero della Salute","doi-asserted-by":"publisher","award":["5 \u00d7\u20091000 project 2017"],"award-info":[{"award-number":["5 \u00d7\u20091000 project 2017"]}],"id":[{"id":"10.13039\/501100003196","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003196","name":"Ministero della Salute","doi-asserted-by":"publisher","award":["\u201cSOLAR: Sleep disorders i"],"award-info":[{"award-number":["\u201cSOLAR: Sleep disorders i"]}],"id":[{"id":"10.13039\/501100003196","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Epilepsia"],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>Sleep\u2010related hypermotor epilepsy (SHE) is a focal epilepsy with seizures occurring mostly during sleep. SHE seizures present different motor characteristics ranging from dystonic posturing to hyperkinetic motor patterns, sometimes associated with affective symptoms and complex behaviors. Disorders of arousal (DOA) are sleep disorders with paroxysmal episodes that may present analogies with SHE seizures. Accurate interpretation of the different SHE patterns and their differentiation from DOA manifestations can be difficult and expensive, and can require highly skilled personnel not always available. Furthermore, it is operator dependent.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Common techniques for human motion analysis, such as wearable sensors (e.g., accelerometers) and motion capture systems, have been considered to overcome these problems. Unfortunately, these systems are cumbersome and they require trained personnel for marker and sensor positioning, limiting their use in the epilepsy domain. To overcome these problems, recently significant effort has been spent in studying automatic methods based on video analysis for the characterization of human motion. Systems based on computer vision and deep learning have been exploited in many fields, but epilepsy has received limited attention.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this paper, we present a pipeline composed of a set of three\u2010dimensional convolutional neural networks that, starting from video recordings, reached an overall accuracy of 80% in the classification of different SHE semiology patterns and DOA.<\/jats:p><\/jats:sec><jats:sec><jats:title>Significance<\/jats:title><jats:p>The preliminary results obtained in this study highlight that our deep learning pipeline could be used by physicians as a tool to support them in the differential diagnosis of the different patterns of SHE and DOA, and encourage further investigation.<\/jats:p><\/jats:sec>","DOI":"10.1111\/epi.17605","type":"journal-article","created":{"date-parts":[[2023,4,4]],"date-time":"2023-04-04T07:46:31Z","timestamp":1680594391000},"page":"1653-1662","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Automatic video analysis and classification of sleep\u2010related hypermotor seizures and disorders of arousal"],"prefix":"10.1111","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8644-0175","authenticated-orcid":false,"given":"Matteo","family":"Moro","sequence":"first","affiliation":[{"name":"Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS) University of Genoa  Genoa Italy"},{"name":"Machine Learning Genoa (MaLGa) Center University of Genoa  Genoa Italy"},{"name":"Robotics and AI for Socio\u2010economic Empowerment (RAISE) Ecosystem  Genoa Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vito Paolo","family":"Pastore","sequence":"additional","affiliation":[{"name":"Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS) University of Genoa  Genoa Italy"},{"name":"Machine Learning Genoa (MaLGa) Center University of Genoa  Genoa Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giorgia","family":"Marchesi","sequence":"additional","affiliation":[{"name":"Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS) University of Genoa  Genoa Italy"},{"name":"Robotics and AI for Socio\u2010economic Empowerment (RAISE) Ecosystem  Genoa Italy"},{"name":"Movendo Technology  Genoa Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paola","family":"Proserpio","sequence":"additional","affiliation":[{"name":"\u201cC. 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