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• W4223579305 startingPage "109597" @default.
• W4223579305 abstract "In recent years, numerous studies on the brain-computer interface (BCI) have been published. However, the number of targets in most of the existing studies was not enough for many practical applications. To achieve highly efficient communications, this study proposed a 120-target BCI system based on code-modulated visual evoked potentials (c-VEPs). Four 31-bit pseudorandom codes were used, and each code generated 30 targets by cyclic shift with a lag of 1 bit. In the online experiments, subjects could select one target in 1.04 s (0.52 s for stimulation and 0.52 s for gaze shifting) with an average information transfer rate (ITR) of 265.74 bits/min. The proposed system achieved more targets and higher ITR than other recent c-VEP based studies. which attributes to the optimal code combination and the 1-bit lag. The results illustrate that the proposed BCI system can achieve a high ITR with a short stimulation time. In addition, the c-VEP paradigm can shorten the training time, which ensures practicality in real applications." @default.
• W4223579305 created "2022-04-15" @default.
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• W4223579305 date "2022-06-01" @default.
• W4223579305 modified "2023-09-27" @default.
• W4223579305 title "A 120-target brain-computer interface based on code-modulated visual evoked potentials" @default.
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• W4223579305 doi "https://doi.org/10.1016/j.jneumeth.2022.109597" @default.
• W4223579305 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35427686" @default.
• W4223579305 hasPublicationYear "2022" @default.
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