A Review of Non Invasive Methods of Brain Activity Measurements via EEG Signals Analysis

Abstract

In neuroscience, electroencephalography (EEG) is a non-invasive method of measuring and monitoring the brain electrical activity by recording the potentials of electrodes placed at standard positions on the scalp. The EEG has become an essential tool for diagnosing and monitoring neurological, cognitive, emotional and even psychological disorders (epilepsy, anesthesia, …). In this paper, we will present an overview of the several methods used for the analysis of EEG signals such as spectral analysis, techniques based on the response to electrical, acoustic or mechanical stimulation, such AEP (Acoustic Evoked Potential) and ERP (Event Related Potential) without forgetting the methods of separation based on independent components analysis (ICA) to identify the different cerebral sources and eliminate the artifacts. Finally, we give an overview on machine learning and artificial intelligence techniques applied to the analysis of EEG signals and Brain computer interface (BCI). To illustrate the results of the EEG analysis, we will present an example of simulation applied to real samples.