Literature DB >> 1375549

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

M Nakamura1, H Shibasaki, K Imajoh, S Nishida, R Neshige, A Ikeda.   

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.

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Year:  1992        PMID: 1375549     DOI: 10.1016/0013-4694(92)90047-l

Source DB:  PubMed          Journal:  Electroencephalogr Clin Neurophysiol        ISSN: 0013-4694


  3 in total

1.  Automatic interpretation of hyperventilation-induced electroencephalogram constructed in the way of qualified electroencephalographer's visual inspection.

Authors:  Xiu Zhang; Xingyu Wang; Takenao Sugi; Akio Ikeda; Takashi Nagamine; Hiroshi Shibasaki; Masatoshi Nakamura
Journal:  Med Biol Eng Comput       Date:  2010-10-12       Impact factor: 2.602

2.  Electrocortical signs of arousal in response to darkness and the assessment of Type A behavior in professional drivers with and without cardiovascular disease.

Authors:  R Emdad
Journal:  Integr Physiol Behav Sci       Date:  1998 Jul-Sep

3.  Computer-assisted interpretation of the EEG background pattern: a clinical evaluation.

Authors:  Shaun S Lodder; Jessica Askamp; Michel J A M van Putten
Journal:  PLoS One       Date:  2014-01-24       Impact factor: 3.240

  3 in total

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