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Preliminary Comparative Experiments of Support Vector Machine and Neural Network for EEG-based BCI Mobile Robot Control

Yasushi Bandou, Takuya Hayakawa, Jun Kobayashi

Year
2019
Citations
2

Abstract

Here we present experimental results of Electroencephalogram (EEG)-based Brain Computer Interface (BCI) for mobile robot control by means of Support Vector Machine (SVM) and Neural Network (NN). The authors had trained NNs using EEGs collected from subjects and verified the performance as BCI; however, the results were unsatisfactory for practical use. In this study, we have used SVM with Radial Basis Function (RBF) kernel function for further improvement and compared the performance with the NNs. Consequently, the SVMs outperformed the NNs in almost all cases.

Keywords

Brain–computer interfaceComputer scienceElectroencephalographySupport vector machineArtificial neural networkArtificial intelligenceMobile robotRobotPsychologyNeuroscience

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