Design of a BCI System for Piloting a Wheelchair Using Five Class MI Based EEG

Motor imagery is the recreation of a motor activity which can be used to design Brain Computer Interfaces (BCI). A BCI bypasses the neuromuscular system and provides a communication link, which directly connects the human brain to an external device. Each individual is able to control his EEG through imaginary motor act it supports to control devices. In this work for designing a BCI system five class motor imagery EEG is used. EEG recorded from the sensory motor cortex is analyzed using wavelet transform. Features extracted from the wavelet coefficients are classified using Support Vector Machine. In this work the motor imagery EEG signal is translated into control signal using a five class BCI to control the directional movement of a wheelchair.