A PCA Aided Cross-Covariance Scheme for Discriminative Feature Extraction from EEG Signals

Brain-Computer Interface (BCI) is a communication system that provides a direct communication channel for transmitting messages from the human brain to computers by analyzing the brain ’s mental activities [1]. Electroencephalogram (EEG) is widely used for the acquisition of brain signals in BCI systems, as it is non-invasive and has excellent temporal resolution [2,3]. Non-invasive BCI systems make the use of EEG signals to translate a subject’s thought or intention into a co ntrol signal that allows a subject, such as a disabled person, to communicate with a device, such as a computer, a wheelchair or a neuroprosthesis [4].

Source: Computer Methods and Programs in Biomedicine - May 24, 2017 Category: Bioinformatics Authors: Roozbeh Zarei, Jing He, Siuly Siuly, Yanchun Zhang Source Type: research