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For: Schaeffer MC, Aksenova T. Data-Driven Transducer Design and Identification for Internally-Paced Motor Brain Computer Interfaces: A Review. Front Neurosci 2018;12:540. [PMID: 30158847 PMCID: PMC6104172 DOI: 10.3389/fnins.2018.00540] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 07/17/2018] [Indexed: 11/13/2022]  Open
Number Cited by Other Article(s)
1
Identifying Thematics in a Brain-Computer Interface Research. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2023;2023:2793211. [PMID: 36643889 PMCID: PMC9833923 DOI: 10.1155/2023/2793211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/21/2022] [Accepted: 12/24/2022] [Indexed: 01/05/2023]
2
Eliseyev A, Aksenova T. Personalized adaptive instruction design (PAID) for brain–computer interface using reinforcement learning and deep learning: simulated data study. BRAIN-COMPUTER INTERFACES 2019. [DOI: 10.1080/2326263x.2019.1651570] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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