This paper includes examples applying EEG data sets to linear and non-linear methods. Also an overview of the various pros and cons of each approach is summarised.

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“Over the past decade, many laboratories have begun to explore brain–computer interface (BCI) technology as a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods.BCI’s provide these users with communication channels that do not depend on peripheral nerves and muscles.”

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“Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals.”

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The authors review classification algorithms used to design brain–computer interface (BCI) systems based on electroencephalography (EEG).

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