Abstract
Brain-Computer Interface (BCI) can convert the electrical activity signal of the cerebral cortex into a computer or other machine language to directly control external equipment. Aiming at the problem of low recognition accuracy of visual stimulation Electroencephalogram (EEG) signals. This paper adopts a method of EEG signal feature extraction based on Synchroextracting Transform (SET). The mean value filter method is used to remove the noise in EEG signal, and the time-frequency energy of EEG signal is taken as the characteristic parameter. Finally, the signal characteristics are input into the SVM model as characteristic parameters. The experimental results show that SET can extract the characteristic energy of EEG signal well and improve the resolution of signal.
Supported by focus on research and development plan in Shandong province (2019JZZY021005).
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Han, L. et al. (2021). Feature Extraction Method of EEG Signal Based on Synchroextracting Transform. In: Fu, W., Xu, Y., Wang, SH., Zhang, Y. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 388. Springer, Cham. https://doi.org/10.1007/978-3-030-82565-2_38
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DOI: https://doi.org/10.1007/978-3-030-82565-2_38
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