Evidence map›Paper›PMID 39313602›Full record

ArticleMedical & biological engineering & computing2025

Filter bank temporally delayed CCA for uncalibrated SSVEP-BCI.

Xiangguo Yin, Caixiu Yang, Hui Dong, Jingting Liang, Mingxing Lin

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Article in Medical & biological engineering & computing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiangguo YinNational Demonstration Center for Experimental Mechanical Engineering Education (Shandong University), Key Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, 250061, Shandong, China.
Caixiu YangThe Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China.
Hui DongNational Demonstration Center for Experimental Mechanical Engineering Education (Shandong University), Key Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, 250061, Shandong, China.
Jingting LiangNational Demonstration Center for Experimental Mechanical Engineering Education (Shandong University), Key Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, 250061, Shandong, China.
Mingxing LinNational Demonstration Center for Experimental Mechanical Engineering Education (Shandong University), Key Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, 250061, Shandong, China. mxlin@sdu.edu.cn.ORCID http://orcid.org/0000-0003-0291-0158

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2024A1515012810
6 · The paper itself

Abstract

The uncalibrated brain-computer interface (BCI) system based on steady-state visual evoked potential (SSVEP) can omit the training process and is closer to the practical application. Filter bank canonical correlation analysis (FBCCA), as a classical approach of uncalibrated SSVEP-based BCI, extracts the fundamental and harmonic ingredients through filter bank decomposition. Nevertheless, this method fails to fully leverage the temporal feature of the signal. The paper suggested utilizing reconstructed data with temporal delay in the computation of the canonical correlation coefficient, and the different combinations of the time-delayed embedding and FBCCA were discussed. We selected the data from seven participants in the Benchmark dataset for parameter optimization and evaluated the method across all participants. The experimental results showed that only embedding the time-delayed version into the first subband (FBdCCA) was better than embedding it into all subbands (FBdCCA(all)), and the accuracy of FBdCCA surpassed that of FBCCA significantly. This suggests that the approach of time-delayed embedding can further enhance the performance of FBCCA.

Indexed as

Brain-Computer InterfacesEvoked Potentials, VisualSignal Processing, Computer-AssistedAdultAlgorithmsElectroencephalographyFemaleHumansMaleTime FactorsYoung AdultCanonical correlation analysis (CCA)Filter bank decompositionSteady-state visual evoked potential (SSVEP)Time-delayed embedding

Identifiers

PMID39313602

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.