{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T19:53:46Z","timestamp":1792007626739,"version":"4.4.0"},"reference-count":53,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T00:00:00Z","timestamp":1767139200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003086","name":"Basque Government","doi-asserted-by":"crossref","award":["IT1489-22"],"award-info":[{"award-number":["IT1489-22"]}],"id":[{"id":"10.13039\/501100003086","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Knowledge Generation Projects of Spain","award":["MCIU-NO23\/P22"],"award-info":[{"award-number":["MCIU-NO23\/P22"]}]},{"DOI":"10.13039\/501100003451","name":"University of the Basque Country","doi-asserted-by":"crossref","award":["PES22\/30"],"award-info":[{"award-number":["PES22\/30"]}],"id":[{"id":"10.13039\/501100003451","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003451","name":"University of the Basque Country","doi-asserted-by":"crossref","award":["EHU-I25\/07"],"award-info":[{"award-number":["EHU-I25\/07"]}],"id":[{"id":"10.13039\/501100003451","id-type":"DOI","asserted-by":"crossref"}]},{"name":"COST Actions","award":["CA22162"],"award-info":[{"award-number":["CA22162"]}]},{"name":"COST Actions","award":["CA22103"],"award-info":[{"award-number":["CA22103"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Background: Essential tremor (ET) is among the most common neurological disorders, requiring precise diagnosis and severity assessment for personalized and effective management. Methods: This study explores an innovative approach to evaluate ET severity using the gold-standard Archimedes spiral test. The family-based dataset covers the entire range of tremor severity, from very mild (level 1) to advanced stages, offering a valuable resource for studying early diagnosis and tracking disease progression. The proposed method introduces a machine learning pipeline that combines Principal Component Analysis (PCA), linear discriminant analysis (LDA), and support vector machines (SVMs) to classify ET severity based on Archimedean spiral radius data. Results: By incorporating the Fahn\u2013Tolosa\u2013Marin Tremor Rating Scale (FMT-TRS), the pipeline effectively distinguishes between tremor presence and severity. Its robustness was demonstrated through rigorous cross-validation and tests involving Gaussian noise perturbations. Conclusions: These results underscore the machine learning-based pipeline\u2019s potential as a non-invasive and trustworthy diagnostic tool for clinical use and telemedicine applications. Moreover, the combination of geometric features, FMT-TRS scores, clinically oriented evaluation metrics, and classical statistical and machine learning models offers a robust, interpretable, explainable, and clinically meaningful analytical framework.<\/jats:p>","DOI":"10.3390\/s26010244","type":"journal-article","created":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T14:33:25Z","timestamp":1767191605000},"page":"244","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Essential Tremor Severity Assessment Using Handwriting Analysis and Machine Learning"],"prefix":"10.3390","volume":"26","author":[{"given":"Jose Ignacio","family":"S\u00e1nchez M\u00e9ndez","sequence":"first","affiliation":[{"name":"NTT DATA EU & LATAM USA Branch Inc., 4100 North Fairfax Drive, Suite 810, Arlington, TX 22203, USA"},{"name":"EleKin Research Group, University of the Basque Country (EHU), 20018 Donostia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9142-7752","authenticated-orcid":false,"given":"Elsa","family":"Fernandez","sequence":"additional","affiliation":[{"name":"EleKin Research Group, University of the Basque Country (EHU), 20018 Donostia, Spain"},{"name":"Department of Computational Science and Artificial Intelligence, University of the Basque Country (EHU), 20018 Donostia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6055-1061","authenticated-orcid":false,"given":"Alberto","family":"Bergareche","sequence":"additional","affiliation":[{"name":"Movement Disorders Unit, Department of Neurology, University Hospital Donostia, Paseo Doctor Begiristain, 109, 20014 Donostia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2135-2393","authenticated-orcid":false,"given":"Karmele","family":"Lopez-de-Ipina","sequence":"additional","affiliation":[{"name":"EleKin Research Group, University of the Basque Country (EHU), 20018 Donostia, Spain"},{"name":"Department of Systems Engineering and Automation, University of the Basque Country (EHU), 20018 Donostia, Spain"},{"name":"Department of Psychiatry, University of Cambridge, Herchel Smith Building Forvie Site Robinson Way Cambridge, Cambridge CB2 0SZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1002\/mds.22838","article-title":"How Common Is the Most Common Adult Movement Disorder? 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