{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T17:21:35Z","timestamp":1789147295174,"version":"build-2803163510"},"reference-count":31,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,3,17]],"date-time":"2024-03-17T00:00:00Z","timestamp":1710633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Department of Energy Sciences and Mechanics"},{"name":"Department of Electrical, Electronics, and Telecommunications Engineering at the Universidad de las Fuerzas Armadas"},{"name":"Department of Mechanical Engineering at the Universidad Polit\u00e9cnica Nacional"},{"name":"Universidad del Valle"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper explores the potential benefits of integrating a brain\u2013computer interface (BCI) utilizing the visual-evoked potential paradigm (SSVEP) with a six-degrees-of-freedom (6-DOF) robotic arm to enhance rehabilitation tools. The SSVEP-BCI employs electroencephalography (EEG) as a method of measuring neural responses inside the occipital lobe in reaction to pre-established visual stimulus frequencies. The BCI offline and online studies yielded accuracy rates of 75% and 83%, respectively, indicating the efficacy of the system in accurately detecting and capturing user intent. The robotic arm achieves planar motion by utilizing a total of five control frequencies. The results of this experiment exhibited a high level of precision and consistency, as indicated by the recorded values of \u00b10.85 and \u00b11.49 cm for accuracy and repeatability, respectively. Moreover, during the performance tests conducted with the task of constructing a square within each plane, the system demonstrated accuracy of 79% and 83%. The use of SSVEP-BCI and a robotic arm together shows promise and sets a solid foundation for the development of assistive technologies that aim to improve the health of people with amyotrophic lateral sclerosis, spina bifida, and other related diseases.<\/jats:p>","DOI":"10.3390\/s24061922","type":"journal-article","created":{"date-parts":[[2024,3,18]],"date-time":"2024-03-18T04:25:15Z","timestamp":1710735915000},"page":"1922","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Assistance Device Based on SSVEP-BCI Online to Control a 6-DOF Robotic Arm"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4317-9844","authenticated-orcid":false,"given":"Maritza","family":"Alb\u00e1n-Escobar","sequence":"first","affiliation":[{"name":"Department of Energy and Mechanics Sciences, Universidad de las Fuerzas Armadas, Sangolqui 171103, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7887-0781","authenticated-orcid":false,"given":"Pablo","family":"Navarrete-Arroyo","sequence":"additional","affiliation":[{"name":"Department of Energy and Mechanics Sciences, Universidad de las Fuerzas Armadas, Sangolqui 171103, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7800-0455","authenticated-orcid":false,"given":"Danni Rodrigo","family":"De la Cruz-Guevara","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronics and Telecommunications Engineering, Universidad de las Fuerzas Armadas, Sangolqui 171103, Ecuador"},{"name":"Department of Mechanical Engineering, Escuela Polit\u00e9cnica Nacional, Quito 170525, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1442-5726","authenticated-orcid":false,"given":"Johanna","family":"Tobar-Quevedo","sequence":"additional","affiliation":[{"name":"Department of Energy and Mechanics Sciences, Universidad de las Fuerzas Armadas, Sangolqui 171103, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1737","DOI":"10.1109\/TNSRE.2022.3185262","article-title":"SSVEP-Based Brain Computer Interface Controlled Soft Robotic Glove for Post-Stroke Hand Function Rehabilitation","volume":"30","author":"Guo","year":"2022","journal-title":"IEEE Trans. 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