脳波モデルを用いた優位律動の特徴表現と背景脳波の自動判読

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The development of an automatic electroencephalogram (EEG) interpretation method is desired to reduce the labor of electroencephalographers. We have already proposed an EEG model that consists of sinusoidal waves with Markov process amplitude to represent the characteristics of the background EEG quantitatively. An automatic interpretation method for the background EEG was previously developed by some of the authors, and the results of the method brought satisfactory coincidence with the results interpreted by a qualified electroencephalographer. However, when the EEG is recorded with trend artifacts, it is highly probable that using the method could result in misjudgment. In this study, an automatic EEG interpretation method using an EEG model is proposed to improve the accuracy of judgment. First, the "period of amplitude variability of dominant rhythm" and "organization of dominant rhythm", which are important factors in EEG interpretation, are represented quantitatively using EEG model parameters. Using the relationships between the model parameters and the characteristics of dominant rhythm, an automatic EEG interpretation method using the EEG model is proposed. In the proposed method, an EEG model that takes account of trend artifacts is constructed to separate the trend artifacts from the background EEG, and specific EEG parameters for each judgment are calculated from the EEG model parameters. The proposed method was applied to actual EEG data, and the results compared with those obtained by the previous automatic EEG interpretation method. The proposed method provided improved judgment for EEG data contaminated with trend artifacts, although misjudgments were reported in the previous method. Furthermore, the proposed method can judge the "organization of dominant rhythm" much more accurately than the previous method.
社団法人日本生体医工学会の論文
2005-09-10

脳波モデルを用いた優位律動の特徴表現と背景脳波の自動判読

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