SSVEP-EEG Signal Classification based on Emotiv EPOC BCI and Raspberry Pi
نویسندگان
چکیده
This work presents the experimental design for recording Electroencephalography (EEG) signals in 20 test subjects submitted to Steady-state visually evoked potential (SSVEP). The stimuli were performed with frequencies of 7, 9, 11 and 13 Hz. Furthermore, implementation a classification system based on SSVEP-EEG from occipital region brain obtained Emotiv EPOC device is presented. These data used train algorithms artificial intelligence Raspberry Pi 4 Model B. Finally, this demonstrates possibility classifying times up 1.8 ms embedded systems low computational capacity.
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ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2021
ISSN: ['2405-8963', '2405-8971']
DOI: https://doi.org/10.1016/j.ifacol.2021.10.287