{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T03:00:54Z","timestamp":1781924454746,"version":"3.54.5"},"reference-count":15,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2023,5,2]],"date-time":"2023-05-02T00:00:00Z","timestamp":1682985600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Sleep Research"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>Excessive fragmentary myoclonus (EFM) is an incidental polysomnographic finding requiring documentation of \u226520\u2009minutes of NREM sleep with \u22655 fragmentary myoclonus (FM) potentials per minute. Manual FM scoring is time\u2010consuming and prone to inter\u2010rater variability. This work aimed to validate an automatic algorithm to score FM in whole\u2010night recordings. One expert scorer manually scored FM in the anterior tibialis muscles in 10 polysomnographies of as many subjects. The algorithm consisted of two steps. First, parameters of the automatic leg movement identification algorithm of the BrainRT software (OSG, Belgium) were modified to identify FM\u2010like activity. Second, a post\u2010processing algorithm was implemented to remove FM activity not meeting sufficient amplitude criteria. The parameter choice and the post\u2010processing were optimised with leave\u2010one\u2010out cross\u2010validation. Agreement with the human scorer was measured with Cohen's kappa (k) and correlation between manual and automatic FM indices in different sleep stages was evaluated. Agreement in identifying patients with EFM was computed. The algorithm showed substantial agreement (average k\u2009&gt;\u20090.62) for all sleep stages, except for W, where a moderate agreement was observed (average k\u2009=\u20090.58). Nonetheless, the agreement between human scorer and the algorithm was similar to previously reported values of inter\u2010rater variability for FM scoring. Correlation coefficients were over 0.96 for all sleep stages. Furthermore, the presence\/absence of EFM was correctly identified in 80% of the subjects. In conclusion, this work presents a reliable algorithm for automatic scoring of FM and EFM. Future studies will apply it to objectively and consistently evaluate FM indices and the presence of EFM in large populations.<\/jats:p>","DOI":"10.1111\/jsr.13921","type":"journal-article","created":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T06:24:25Z","timestamp":1683095065000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A reliable automatic algorithm to score fragmentary myoclonus"],"prefix":"10.1111","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0097-4396","authenticated-orcid":false,"given":"Melanie","family":"Bergmann","sequence":"first","affiliation":[{"name":"Department of Neurology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1894-7641","authenticated-orcid":false,"given":"Birgit","family":"H\u00f6gl","sequence":"additional","affiliation":[{"name":"Department of Neurology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abubaker","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Department of Neurology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elisabeth","family":"Brandauer","sequence":"additional","affiliation":[{"name":"Department of Neurology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9552-7619","authenticated-orcid":false,"given":"Anna","family":"Heidbreder","sequence":"additional","affiliation":[{"name":"Department of Neurology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4259-8824","authenticated-orcid":false,"given":"Ambra","family":"Stefani","sequence":"additional","affiliation":[{"name":"Department of Neurology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6554-1033","authenticated-orcid":false,"given":"Matteo","family":"Cesari","sequence":"additional","affiliation":[{"name":"Department of Neurology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,5,2]]},"reference":[{"key":"e_1_2_8_2_1","volume-title":"International classification of sleep disorders","author":"American Academy of Sleep Medicine","year":"2014"},{"key":"e_1_2_8_3_1","volume-title":"The AASM manual for the scoring of sleep and associated events: Rules, terminology and technical specifications: Version 2.6","author":"Berry R. 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