Emergence of artificial intelligence in electroencephalogram analysis

Abstract

Electroencephalography (EEG) is a noninvasive method used in cognitive neuroscience and clinical neurology for the assessment of cerebral activity. Despite significant technological advancements in EEG, it has always depended on manual examination and conventional signal processing, both of which are complexes and laborious. The advent of artificial intelligence (AI) has significantly influenced EEG analysis by allowing automated features extraction and complex modeling of sophisticated brain signals. Machine learning (ML) and deep learning (DL) approaches now augment EEG-based diagnostics, cognitive evaluations and clinical neurology applications.