Detection of characteristic waves of sleep EEG by neural network analysis

Takamasa Shimada, Tsuyoshi Shiina, Yoichi Saito

研究成果: Article査読

57 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)369-379
ページ数11
ジャーナルIEEE Transactions on Biomedical Engineering
47
3
DOI
出版ステータスPublished - 2000
外部発表はい

ASJC Scopus subject areas

  • 生体医工学

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