{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T11:33:26Z","timestamp":1768822406653,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T00:00:00Z","timestamp":1675987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007065","name":"University of Salerno","doi-asserted-by":"publisher","award":["FARB2019"],"award-info":[{"award-number":["FARB2019"]}],"id":[{"id":"10.13039\/501100007065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The aim of this study was to determine a gait pattern, i.e., a subset of spatial and temporal parameters, through a supervised machine learning (ML) approach, which could be used to reliably distinguish Parkinson\u2019s Disease (PD) patients with and without mild cognitive impairment (MCI). Thus, 80 PD patients underwent gait analysis and spatial\u2013temporal parameters were acquired in three different conditions (normal gait, motor dual task and cognitive dual task). Statistical analysis was performed to investigate the data and, then, five ML algorithms and the wrapper method were implemented: Decision Tree (DT), Random Forest (RF), Na\u00efve Bayes (NB), Support Vector Machine (SVM) and K-Nearest Neighbour (KNN). First, the algorithms for classifying PD patients with MCI were trained and validated on an internal dataset (sixty patients) and, then, the performance was tested by using an external dataset (twenty patients). Specificity, sensitivity, precision, accuracy and area under the receiver operating characteristic curve were calculated. SVM and RF showed the best performance and detected MCI with an accuracy of over 80.0%. The key features emerging from this study are stance phase, mean velocity, step length and cycle length; moreover, the major number of features selected by the wrapper belonged to the cognitive dual task, thus, supporting the close relationship between gait dysfunction and MCI in PD.<\/jats:p>","DOI":"10.3390\/s23041985","type":"journal-article","created":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T04:48:03Z","timestamp":1676004483000},"page":"1985","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Identification of a Gait Pattern for Detecting Mild Cognitive Impairment in Parkinson\u2019s Disease"],"prefix":"10.3390","volume":"23","author":[{"given":"Michela","family":"Russo","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}]},{"given":"Marianna","family":"Amboni","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84081 Baronissi, Italy"},{"name":"IDC Hermitage Capodimonte, 80133 Naples, Italy"}]},{"given":"Paolo","family":"Barone","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84081 Baronissi, Italy"}]},{"given":"Maria Teresa","family":"Pellecchia","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84081 Baronissi, Italy"}]},{"given":"Maria","family":"Romano","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7290-6432","authenticated-orcid":false,"given":"Carlo","family":"Ricciardi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9053-3139","authenticated-orcid":false,"given":"Francesco","family":"Amato","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1007\/s00702-017-1686-y","article-title":"Epidemiology of Parkinson\u2019s Disease","volume":"124","author":"Tysnes","year":"2017","journal-title":"J. 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