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Progresses and prospects on frequency recognition methods for steady-state visual evoked potential / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 192-197, 2022.
Artículo en Chino | WPRIM | ID: wpr-928214
ABSTRACT
Steady-state visual evoked potential (SSVEP) is one of the commonly used control signals in brain-computer interface (BCI) systems. The SSVEP-based BCI has the advantages of high information transmission rate and short training time, which has become an important branch of BCI research field. In this review paper, the main progress on frequency recognition algorithm for SSVEP in past five years are summarized from three aspects, i.e., unsupervised learning algorithms, supervised learning algorithms and deep learning algorithms. Finally, some frontier topics and potential directions are explored.
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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Asunto principal: Estimulación Luminosa / Algoritmos / Electroencefalografía / Potenciales Evocados Visuales / Interfaces Cerebro-Computador Idioma: Chino Revista: Journal of Biomedical Engineering Año: 2022 Tipo del documento: Artículo

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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Asunto principal: Estimulación Luminosa / Algoritmos / Electroencefalografía / Potenciales Evocados Visuales / Interfaces Cerebro-Computador Idioma: Chino Revista: Journal of Biomedical Engineering Año: 2022 Tipo del documento: Artículo