Literature DB >> 3916845

Automatic recognition and characterization of epileptiform discharges in the human EEG.

J D Frost1.   

Abstract

Methods proposed for the automatic identification and quantification of epileptiform EEG activity are reviewed, and the potential role of this technology in clinical electroencephalography is assessed. Techniques developed for the detection of spikes, sharp waves, and spike and wave complexes are described. Emphasis is placed on the problems associated with artifact rejection and the need for establishing context-based decision-making processes.

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Year:  1985        PMID: 3916845     DOI: 10.1097/00004691-198507000-00003

Source DB:  PubMed          Journal:  J Clin Neurophysiol        ISSN: 0736-0258            Impact factor:   2.177


  2 in total

1.  Use of discrete Hilbert transformation for automatic spike mapping: a methodological investigation.

Authors:  H Witte; M Eiselt; I Patakova; S Petranek; G Griessbach; V Krajca; M Rother
Journal:  Med Biol Eng Comput       Date:  1991-05       Impact factor: 2.602

2.  Spike detection in biomedical signals using midprediction filter.

Authors:  S Dandapat; G C Ray
Journal:  Med Biol Eng Comput       Date:  1997-07       Impact factor: 2.602

  2 in total

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