{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T21:42:45Z","timestamp":1767994965642,"version":"3.49.0"},"reference-count":52,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2020,8,10]],"date-time":"2020-08-10T00:00:00Z","timestamp":1597017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministerio de Econom\u00eda y Competitividad (MINECO), Spain","award":["TEC2016-78028-C3-2-P"],"award-info":[{"award-number":["TEC2016-78028-C3-2-P"]}]},{"name":"Ministerio de Ciencia, Innovacion y Universidades, Spain","award":["PGC2018-0971-B-100"],"award-info":[{"award-number":["PGC2018-0971-B-100"]}]},{"name":"Fundacion Seneca de la Region de Murcia, Spain","award":["20783\/PI\/18"],"award-info":[{"award-number":["20783\/PI\/18"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Motor imagery (MI)-based brain-computer interface (BCI) systems detect electrical brain activity patterns through electroencephalogram (EEG) signals to forecast user intention while performing movement imagination tasks. As the microscopic details of individuals\u2019 brains are directly shaped by their rich experiences, musicians can develop certain neurological characteristics, such as improved brain plasticity, following extensive musical training. Specifically, the advanced bimanual motor coordination that pianists exhibit means that they may interact more effectively with BCI systems than their non-musically trained counterparts; this could lead to personalized BCI strategies according to the users\u2019 previously detected skills. This work assessed the performance of pianists as they interacted with an MI-based BCI system and compared it with that of a control group. The Common Spatial Patterns (CSP) and Linear Discriminant Analysis (LDA) machine learning algorithms were applied to the EEG signals for feature extraction and classification, respectively. The results revealed that the pianists achieved a higher level of BCI control by means of MI during the final trial (74.69%) compared to the control group (63.13%). The outcome indicates that musical training could enhance the performance of individuals using BCI systems.<\/jats:p>","DOI":"10.3390\/s20164452","type":"journal-article","created":{"date-parts":[[2020,8,10]],"date-time":"2020-08-10T07:25:03Z","timestamp":1597044303000},"page":"4452","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["On the Better Performance of Pianists with Motor Imagery-Based Brain-Computer Interface Systems"],"prefix":"10.3390","volume":"20","author":[{"given":"Jos\u00e9-Vicente","family":"Riquelme-Ros","sequence":"first","affiliation":[{"name":"Consejer\u00eda de Educaci\u00f3n y Cultura de la Regi\u00f3n de Murcia, E30003 Murcia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3121-1532","authenticated-orcid":false,"given":"Germ\u00e1n","family":"Rodr\u00edguez-Berm\u00fadez","sequence":"additional","affiliation":[{"name":"University Center of Defense, San Javier Air Force Base, Ministerio de Defensa-Universidad Polit\u00e9cnica de Cartagena, E30720 Santiago de la Ribera, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0118-3406","authenticated-orcid":false,"given":"Ignacio","family":"Rodr\u00edguez-Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda de Comunicaciones, ATIC Research Group, Universidad de M\u00e1laga, E29071 M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3298-6439","authenticated-orcid":false,"given":"Jos\u00e9-V\u00edctor","family":"Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Departamento de Tecnolog\u00edas de la Informaci\u00f3n y las Comunicaciones, Universidad Polit\u00e9cnica de Cartagena, E30202 Cartagena, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6415-7363","authenticated-orcid":false,"given":"Jos\u00e9-Mar\u00eda","family":"Molina-Garc\u00eda-Pardo","sequence":"additional","affiliation":[{"name":"Departamento de Tecnolog\u00edas de la Informaci\u00f3n y las Comunicaciones, Universidad Polit\u00e9cnica de Cartagena, E30202 Cartagena, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.3390\/s120201211","article-title":"Brain computer interfaces, a review","volume":"12","year":"2012","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.eij.2015.06.002","article-title":"Brain computer interfacing: Applications and challenges","volume":"16","author":"Abdulkader","year":"2015","journal-title":"Egypt. 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