EEG Signal Classification of Motor Imagery Right and Left Hand using Common Spatial Pattern and Multilayer Perceptron Back Propagation

The number of people with disabilities is increasing, so it requires bionic devices to replace human motor functions. Brain-Computer Interface (BCI) can be a tool for the device communicate brain. Signal brain or Electroencephalogram (EEG) signal need classify drive corresponding device. This research goal imagination right and left-hand movements based on EEG signal. system design in this consists channel selection using Finite Impulse Response (FIR) filter, feature extraction Common Spatial Pattern (CSP), classification Multilayer Perceptron Back Propagation (MLP-BP). data used secondary dataset from BCI Competition IV (2b) 9 subjects. scenario carried out by trying use several variations hidden layer nodes each channel. Based test, best accuracy MLP-BP 68.7% 24 alpha