Detection and location of EEG events using deep learning visual inspection.

ABSTRACT: The electroencephalogram (EEG) is a major diagnostic tool that provides detailed insight into the electrical activity of the brain. This signal contains a number of distinctive waveform patterns that reflect the subject's health state in relation to sleep, neurological disorders, memory functions, and more. In this regard, sleep spindles and K-complexes are two major waveform patterns of interest to specialists, who visually inspect the recordings to identify these events. The literature typically follows a traditional approach that examines the time-varying signal to identify features representing the events of interest. Even though most of these methods target individual event types, their reported performance results leave significant room for improvement. The research presented here ad

SUBMITTER: Fraiwan MA 

PROVIDER: S-EPMC11666049 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature