Single channel electroencephalogram feature extraction based on probability density function for synchronous brain computer interface - Shawkany Hazim, M. S. A. (Penerbit UTM Press, 2016)
Over recent years, there has been an explosive growth of interest in Electroencephalogram (EEG) based-Brain Computer Interface (BCI). Technically any architecture of a BCI is designed to have the ability of extracting out a set of features from brain signal. This paper demonstrated the extraction process based on Probability Density Function (PDF).A shared control scheme was developed between a mobile robot and subject. In general, subjects were required to synchronously imagine a star rotating and mind relaxation at specific time and direction. The imagination of a star would trigger a mobile robot suggesting that there is an object at certain direction. The mobile robot was then looking for a target based on probability value assigned to it. The result shows that 95 of theta activity was concentrated at target\x92s direction (during star imagination) and reduced when there is no target (during mind relaxation).