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脑电图自动解读:一种用于清醒状态下背景脑电图自动综合解读的新型计算机辅助系统。

Automatic EEG interpretation: a new computer-assisted system for the automatic integrative interpretation of awake background EEG.

作者信息

Nakamura M, Shibasaki H, Imajoh K, Nishida S, Neshige R, Ikeda A

机构信息

Department of Electrical Engineering, Saga University, Japan.

出版信息

Electroencephalogr Clin Neurophysiol. 1992 Jun;82(6):423-31. doi: 10.1016/0013-4694(92)90047-l.

Abstract

A new computer-assisted system for automatic interpretation of the awake electroencephalogram (EEG) was developed. First, all the items necessary for EEG interpretation were determined in accordance with the procedure that a qualified electroencephalographer (EEGer) goes through for the visual inspection of the background EEG activity, and then each item was defined quantitatively. For the automatic interpretation, specific EEG parameters were determined for each item so that they could fit the graded judgement of the item by the qualified EEGer as closely as possible. These specific EEG parameters were actually calculated from periodograms obtained from the time series of EEG records of 14 patients with various neurological diseases. The automatic EEG interpretation system thus established was applied to the EEG data of these 14 subjects and to 3 additional EEGs, and the results were compared with those obtained through the visual interpretation by the EEGer. This automatic EEG interpretation was found to be in good agreement with the visual interpretation by the EEGer in most EEG records. In contrast with the previous automatic analyses of EEG which were focussed on certain aspects of EEG such as the dominant rhythm, the present system is unique in its capability of providing an integrative interpretation of the spontaneous awake EEG by taking into account all its features except for paroxysmal abnormalities.

摘要

开发了一种用于自动解读清醒脑电图(EEG)的新型计算机辅助系统。首先,根据合格脑电图技师(EEGer)对背景EEG活动进行视觉检查的程序,确定EEG解读所需的所有项目,然后对每个项目进行定量定义。对于自动解读,为每个项目确定特定的EEG参数,以便它们尽可能符合合格EEGer对该项目的分级判断。这些特定的EEG参数实际上是从14名患有各种神经系统疾病患者的EEG记录时间序列的周期图中计算得出的。由此建立的自动EEG解读系统应用于这14名受试者的EEG数据以及另外3份EEG,并将结果与EEGer通过视觉解读获得的结果进行比较。发现在大多数EEG记录中,这种自动EEG解读与EEGer的视觉解读高度一致。与以往专注于EEG某些方面(如主导节律)的自动分析不同,本系统的独特之处在于能够通过考虑除阵发性异常之外的所有特征,对清醒状态下的自发EEG进行综合解读。

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