Autoencoding of long-term scalp electroencephalogram to detect epileptic seizure for diagnosis support system.

Journal: Computers in biology and medicine
PMID:

Abstract

INTRODUCTION: Epileptologists could benefit from a diagnosis support system that automatically detects seizures because visual inspection of long-term electroencephalograms (EEGs) is extremely time-consuming. However, the diversity of seizures among patients makes it difficult to develop universal features that are applicable for automatic seizure detection in all cases, and the rarity of seizures results in a lack of sufficient training data for classifiers.

Authors

  • Ali Emami
    Research Center for Advanced Science and Technology, The University of Tokyo, Japan.
  • Naoto Kunii
  • Takeshi Matsuo
    Tokyo Metropolitan Neurological Hospital, Japan.
  • Takashi Shinozaki
    CiNet, National Institute of Information and Communications Technology, Japan.
  • Kensuke Kawai
  • Hirokazu Takahashi
    Department of Internal MedicineSaga Medical SchoolSaga UniversitySagaJapan.