Classification of EEG from Black Color Stimuli to Command a Remote-Controlled Car: Ongoing Study

摘要

In this manuscript, we present a pilot study to use the black color stimuli and resting state to wirelessly control a remote-controlled car. Power Spectral Density (PSD) was calculated on EEG signals to extract features and Multilayer Perceptron (MLP) was proposed to classify the EEG features using a 5-fold cross validation. Our results reported that best score classification was on 100% for Delta band using six electrodes and they allow to control a remote-controlled car. This approach is compared to other BCI paradigm and machine learning algorithms so that our results outperformed others works.