Detection and location of EEG events using deep learning visual inspection

• Published in: PloS one Vol. 19; no. 12; p. e0312763
• Main Author: Fraiwan, Mohammad Amin
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 23.12.2024; Public Library of Science (PLoS)
• Subjects: Accuracy; Activity patterns; Algorithms; Artificial neural networks; Biology and Life Sciences; Brain - physiology; Classification; Computer and Information Sciences; Datasets; Deep Learning; EEG; Electroencephalography; Electroencephalography - methods; Engineering and Technology; Evaluation; Fourier transforms; Health aspects; Humans; Inspection; Machine learning; Medicine and Health Sciences; Neural networks; Neurological diseases; Object recognition; Performance evaluation; Physical Sciences; Research and Analysis Methods; Sensors; Signal processing; Signal Processing, Computer-Assisted; Sleep; Sleep - physiology; Sleep Stages - physiology; Visual discrimination learning; Waveforms; Wavelet transforms; Jordan

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, a...