Detection of characteristic waves of sleep EEG by neural network analysis

Takamasa Shimada, Tsuyoshi Shiina, Yoichi Saito

Research output: Contribution to journalArticlepeer-review

58 Citations (Scopus)


In psychiatry, the sleep stage is one of the most important evidence for diagnosing mental disease. However, doctors require much labor and skill for diagnosis, so a quantitative and objective method is required for more accurate diagnosis since it depends on the doctor's experience. For this reason, an automatic diagnosis system must be developed. In this paper, we propose a new type of neural network (NN) model referred to as a sleep electroencephalogram (EEG) recognition neural network (SRNN) which enables us to detect several kinds of important characteristic waves in sleep EEG which are necessary for diagnosing sleep stages. Experimental results indicate that the proposed NN model was much more capable than other conventional methods for detecting characteristic waves.

Original languageEnglish
Pages (from-to)369-379
Number of pages11
JournalIEEE Transactions on Biomedical Engineering
Issue number3
Publication statusPublished - 2000
Externally publishedYes


  • Characteristic wave
  • EEG
  • Neural network
  • Sleep stage

ASJC Scopus subject areas

  • Biomedical Engineering


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