{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T03:52:04Z","timestamp":1771905124299,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T00:00:00Z","timestamp":1618963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003500","name":"Universit\u00e0 degli Studi di Padova","doi-asserted-by":"publisher","award":["REPAC project (Initiative SID-Networking 2019)"],"award-info":[{"award-number":["REPAC project (Initiative SID-Networking 2019)"]}],"id":[{"id":"10.13039\/501100003500","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003407","name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca","doi-asserted-by":"publisher","award":["Initiative \"Departments of Excellence\" (Law 232\/2016)"],"award-info":[{"award-number":["Initiative \"Departments of Excellence\" (Law 232\/2016)"]}],"id":[{"id":"10.13039\/501100003407","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Horizon 2020","award":["Project MoreGrasp (\u2019643955\u2019)"],"award-info":[{"award-number":["Project MoreGrasp (\u2019643955\u2019)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>The classification of different fine hand movements from electroencephalogram (EEG) signals represents a relevant research challenge, e.g., in BCI applications for motor rehabilitation. Here, we analyzed two different datasets where fine hand movements (touch, grasp, palmar, and lateral grasp) were performed in a self-paced modality. We trained and tested a newly proposed CNN, and we compared its classification performance with two well-established machine learning models, namely, shrinkage-linear discriminant analysis (LDA) and Random Forest (RF). Compared to previous literature, we included neuroscientific evidence, and we trained our Convolutional Neural Network (CNN) model on the so-called movement-related cortical potentials (MRCPs). They are EEG amplitude modulations at low frequencies, i.e., (0.3,3) Hz that have been proved to encode several properties of the movements, e.g., type of grasp, force level, and speed. We showed that CNN achieved good performance in both datasets (accuracy of 0.70\u00b10.11 and 0.64\u00b10.10, for the two datasets, respectively), and they were similar or superior to the baseline models (accuracy of 0.68\u00b10.10 and 0.62\u00b10.07 with sLDA; accuracy of 0.70\u00b10.15 and 0.61\u00b10.07 with RF, with comparable performance in precision and recall). In addition, compared to the baseline, our CNN requires a faster pre-processing procedure, paving the way for its possible use in online BCI applications.<\/jats:p>","DOI":"10.3390\/fi13050103","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T12:47:07Z","timestamp":1619009227000},"page":"103","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Deep Learning-Based Classification of Fine Hand Movements from Low Frequency EEG"],"prefix":"10.3390","volume":"13","author":[{"given":"Giulia","family":"Bressan","sequence":"first","affiliation":[{"name":"Department of Information Engineering, University of Padova, 35122 Padova, Italy"},{"name":"Institute of Neural Engineering, Graz University of Technology, 8010 Graz, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9554-9367","authenticated-orcid":false,"given":"Giulia","family":"Cisotto","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Padova, 35122 Padova, Italy"},{"name":"National Centre for Neurology and Psychiatry, Tokyo 187-8551, Japan"},{"name":"National Inter-University Consortium for Telecommunications (CNIT), 43124 Parma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0087-3720","authenticated-orcid":false,"given":"Gernot R.","family":"M\u00fcller-Putz","sequence":"additional","affiliation":[{"name":"Institute of Neural Engineering, Graz University of Technology, 8010 Graz, Austria"},{"name":"BioTechMed-Graz, 8010 Graz, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4345-7310","authenticated-orcid":false,"given":"Selina Christin","family":"Wriessnegger","sequence":"additional","affiliation":[{"name":"Institute of Neural Engineering, Graz University of Technology, 8010 Graz, Austria"},{"name":"BioTechMed-Graz, 8010 Graz, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Cisotto, G., Pupolin, S., Silvoni, S., Cavinato, M., Agostini, M., and Piccione, F. 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