Aplicação da Análise de Correlação Canônica em Sistemas ICM Baseados em SSVEP

• Sávio M. Sousa UFPA
• Fablena K. N. Dias UFPA
• Cleison D. Silva UFPA

DOI: https://doi.org/10.5753/erad-no2.2023.236265

Abstract

Brain-Computer Interface (BCI) systems are capable of performing communications between humans and machines through electroencephalogram (EEG) signals that are processed and converted into commands. The focus of this scientific research is on the study of information extraction and processing techniques using the Canonical Correlation Analysis (CCA) method for optimizing ICM systems based on Steady State Visually Evoked Potential (SSVEP). In this research, five approaches were performed using the CCA method, maintaining the same process of data acquisition, pre-processing and classification. In the end, the accuracy of the classifier was used as a parameter for discussions and conclusions.

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