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Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 208-213, 2022 07.
Artigo em Inglês | MEDLINE | ID: mdl-36086083

RESUMO

This study details the development of a novel, approx. £20 electroencephalogram (EEG)-based brain-computer interface (BCI) intended to offer a financially and operationally accessible device that can be deployed on a mass scale to facilitate education and public engagement in the domain of EEG sensing and neurotechnologies. Real-time decoding of steady-state visual evoked potentials (SSVEPs) is achieved using variations of the widely-used canonical correlation analysis (CCA) algorithm: multi-set CCA and generalised CCA. All BCI functionality is executed on board an inexpensive ESP32 microcontroller. SSVEP decoding accuracy of 95.56 ± 3.74% with an ITR of 102 bits/min was achieved with modest calibration.


Assuntos
Interfaces Cérebro-Computador , Potenciais Evocados Visuais , Algoritmos , Calibragem , Eletroencefalografia
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