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Optimizing a dual-frequency and phase modulation method for SSVEP-based BCIs

Liyan Liang, Jiajun Lin, Chen Yang, Yijun Wang, Xiaogang Chen, Shangkai Gao, Xiaorong Gao

2020Journal of Neural Engineering37 citationsDOI

Abstract

OBJECTIVE: The design of the stimulation paradigm plays an important role in steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) studies. Among various stimulation designs, the dual-frequency paradigm in which two frequencies are used to encode one target is of importance and interest. However, because the number of possible frequency combinations is huge, the existing dual-frequency modulation paradigms failed to optimize the encoding towards the best combinations. Thus, this work aiming at designing a new dual-frequency and phase modulation paradigm with the best combinations stimuli. APPROACH: This study proposed a dual-frequency and phase modulation method, which can achieve a large number of targets by making different combinations of two frequencies and an initial phase. This study also designed a set of methods for quickly optimizing the stimulation codes for the dual-frequency and phase modulation method. MAIN RESULTS: , which were much higher than the existing dual-frequency modulation paradigms. Moreover, an offline simulation with a public dataset showed that the optimization method was also effective for optimizing the single-frequency and phase modulation paradigm. SIGNIFICANCE: These results demonstrate the high performance of the proposed dual-frequency and phase modulation method and the high efficiency of the optimization method for designing SSVEP stimulation paradigms. In addition, the coding efficiency of the optimized dual-frequency and phase modulation paradigm is higher than that of the single-frequency and phase modulation paradigm, and it is expected to further realize the BCI paradigm with a large amount of targets.

Topics & Concepts

Computer scienceModulation (music)Frequency modulationCoding (social sciences)Dual (grammatical number)Brain–computer interfaceSet (abstract data type)Phase modulationInformation transferEncoding (memory)Phase (matter)Artificial intelligenceElectroencephalographyMathematicsTelecommunicationsRadio frequencyPhysicsAcousticsLiteraturePsychiatryArtQuantum mechanicsProgramming languageStatisticsPsychologyEEG and Brain-Computer InterfacesPhotoreceptor and optogenetics researchNeuroscience and Neural Engineering
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