{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T22:31:07Z","timestamp":1779921067993,"version":"3.53.1"},"reference-count":42,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,23]],"date-time":"2022-08-23T00:00:00Z","timestamp":1661212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The detection analysis of neurodegenerative diseases by means of low-cost sensors and suitable classification algorithms is a key part of the widely spreading telemedicine techniques. The choice of suitable sensors and the tuning of analysis algorithms require a large amount of data, which could be derived from a large experimental measurement campaign involving voluntary patients. This process requires a prior approval phase for the processing and the use of sensitive data in order to respect patient privacy and ethical aspects. To obtain clearance from an ethics committee, it is necessary to submit a protocol describing tests and wait for approval, which can take place after a typical period of six months. An alternative consists of structuring, implementing, validating, and adopting a software simulator at most for the initial stage of the research. To this end, the paper proposes the development, validation, and usage of a software simulator able to generate movement disorders-related data, for both healthy and pathological conditions, based on raw inertial measurement data, and give tri-axial acceleration and angular velocity as output. To present a possible operating scenario of the developed software, this work focuses on a specific case study, i.e., the Parkinson\u2019s disease-related tremor, one of the main disorders of the homonym pathology. The full framework is reported, from raw data availability to pathological data generation, along with a common machine learning method implementation to evaluate data suitability to be distinguished and classified. Due to the development of a flexible and easy-to-use simulator, the paper also analyses and discusses the data quality, described with typical measurement features, as a metric to allow accurate classification under a low-performance sensing device. The simulator\u2019s validation results show a correlation coefficient greater than 0.94 for angular velocity and 0.93 regarding acceleration data. Classification performance on Parkinson\u2019s disease tremor was greater than 98% in the best test conditions.<\/jats:p>","DOI":"10.3390\/s22176341","type":"journal-article","created":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T02:55:34Z","timestamp":1661309734000},"page":"6341","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Development and Assessment of a Movement Disorder Simulator Based on Inertial Data"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0151-7274","authenticated-orcid":false,"given":"Chiara","family":"Carissimo","sequence":"first","affiliation":[{"name":"Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6843-7140","authenticated-orcid":false,"given":"Gianni","family":"Cerro","sequence":"additional","affiliation":[{"name":"Department of Medicine and Health Sciences \u201cVincenzo Tiberio\u201d, University of Molise, 86100 Campobasso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1724-5720","authenticated-orcid":false,"given":"Luigi","family":"Ferrigno","sequence":"additional","affiliation":[{"name":"Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8801-1905","authenticated-orcid":false,"given":"Giacomo","family":"Golluccio","sequence":"additional","affiliation":[{"name":"Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9050-9825","authenticated-orcid":false,"given":"Alessandro","family":"Marino","sequence":"additional","affiliation":[{"name":"Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,23]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2022, February 02). 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