Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning.

Journal: BMC medical informatics and decision making
Published Date: Nov 17, 2022

Abstract

BACKGROUND: The electroencephalography (EEG) signal carries important information about the electrical activity of the brain, which may reveal many pathologies. This information is carried in certain waveforms and events, one of which is the K-complex. It is used by neurologists to diagnose neurophysiologic and cognitive disorders as well as sleep studies. Existing detection methods largely depend on tedious, time-consuming, and error-prone manual inspection of the EEG waveform.

Authors

  • Natheer Khasawneh
    Department of Software Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan.
  • Mohammad Fraiwan
    Department of Computer Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan.
  • Luay Fraiwan
    Department of Biomedical Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan.

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