A hybrid CNN-Bi-LSTM model with feature fusion for accurate epilepsy seizure detection.

Journal: BMC medical informatics and decision making
PMID: 39762881

Abstract

BACKGROUND: The diagnosis and treatment of epilepsy continue to face numerous challenges, highlighting the urgent need for the development of rapid, accurate, and non-invasive methods for seizure detection. In recent years, advancements in the analysis of electroencephalogram (EEG) signals have garnered widespread attention, particularly in the area of seizure recognition.

Authors

  • Xiaoshuai Cao
    The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China.
  • Shaojie Zheng
    College of Information Engineering, Henan University of Science and Technology, Luoyang, China.
  • Jincan Zhang
    College of Information Engineering, Henan University of Science and Technology, Luoyang, China.
  • Wenna Chen
    The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China. chenwenna0408@163.com.
  • Ganqin Du
    The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China.

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