{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T00:51:48Z","timestamp":1775868708728,"version":"3.50.1"},"reference-count":77,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,6,6]],"date-time":"2020-06-06T00:00:00Z","timestamp":1591401600000},"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>We present a model for digital neural impairment screening and self-assessment, which can evaluate cognitive and motor deficits for patients with symptoms of central nervous system (CNS) disorders, such as mild cognitive impairment (MCI), Parkinson\u2019s disease (PD), Huntington\u2019s disease (HD), or dementia. The data was collected with an Android mobile application that can track cognitive, hand tremor, energy expenditure, and speech features of subjects. We extracted 238 features as the model inputs using 16 tasks, 12 of them were based on a self-administered cognitive testing (SAGE) methodology and others used finger tapping and voice features acquired from the sensors of a smart mobile device (smartphone or tablet). Fifteen subjects were involved in the investigation: 7 patients with neurological disorders (1 with Parkinson\u2019s disease, 3 with Huntington\u2019s disease, 1 with early dementia, 1 with cerebral palsy, 1 post-stroke) and 8 healthy subjects. The finger tapping, SAGE, energy expenditure, and speech analysis features were used for neural impairment evaluations. The best results were achieved using a fusion of 13 classifiers for combined finger tapping and SAGE features (96.12% accuracy), and using bidirectional long short-term memory (BiLSTM) (94.29% accuracy) for speech analysis features.<\/jats:p>","DOI":"10.3390\/s20113236","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T05:16:14Z","timestamp":1591679774000},"page":"3236","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["A Mobile Application for Smart Computer-Aided Self-Administered Testing of Cognition, Speech, and Motor Impairment"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9013-2602","authenticated-orcid":false,"given":"Andrius","family":"Lauraitis","sequence":"first","affiliation":[{"name":"Department of Multimedia Engineering, Kaunas University of Technology, 50186 Kaunas, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2809-2213","authenticated-orcid":false,"given":"Rytis","family":"Maskeli\u016bnas","sequence":"additional","affiliation":[{"name":"Department of Multimedia Engineering, Kaunas University of Technology, 50186 Kaunas, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9990-1084","authenticated-orcid":false,"given":"Robertas","family":"Dama\u0161evi\u010dius","sequence":"additional","affiliation":[{"name":"Department of Applied Informatics, Vytautas Magnus University, 44404 Kaunas, Lithuania"},{"name":"Faculty of Applied Mathematics, Silesian University of Technology, 44-100 Gliwice, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8509-420X","authenticated-orcid":false,"given":"Tomas","family":"Krilavi\u010dius","sequence":"additional","affiliation":[{"name":"Department of Applied Informatics, Vytautas Magnus University, 44404 Kaunas, Lithuania"},{"name":"Baltic Institute of Advanced Technology, 01124 Vilnius, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1176\/appi.focus.20160043","article-title":"Parkinson\u2019s Disease: Cognitive Impairment","volume":"15","author":"Mack","year":"2017","journal-title":"Focus"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/0093-934X(87)90124-6","article-title":"Speech timing in Parkinson\u2019s and Huntington\u2019s disease","volume":"32","author":"Ludlow","year":"1987","journal-title":"Brain Lang."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1212\/WNL.0b013e3181b04aa2","article-title":"Dietary intake in adults at risk for Huntington disease: Analysis of PHAROS research participants","volume":"73","author":"Marder","year":"2009","journal-title":"Neurology"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1001\/archneurol.2009.217","article-title":"Essential tremors: A family of neurodegenerative disorders?","volume":"66","author":"Louis","year":"2009","journal-title":"Arch. 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