Brain signal classification using normalisation

This chapter focuses on brain computer interface (BCI) brain signal classification. BCI classification is a multistep process which includes: brain signal acquisition: This refers to the brain imaging method used to acquire the brain signal, such as electroencephalography (EEG). Preprocessing during the preprocessing step, various signal processing methods such as digital filtering and artefact removal methods are applied in order to improve signal quality. Feature extraction: during this step useful features in the signal associated with the user’s cognitive state are extracted. Classification: This involves the extracted features to make predictions about the user’s current cognitive state. This can involve machine-learning techniques or other detection algorithms. Device control: this step, commonly known as `translation’, involves converting the classifier outputs into a form usable by the external device.