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

Shaun Lodder, Jessica Askamp, Michel Johannes Antonius Maria van Putten

Research output: Contribution to journalArticleAcademicpeer-review

11 Citations (Scopus)
101 Downloads (Pure)


Objective Interpretation of the EEG background pattern in routine recordings is an important part of clinical reviews. We evaluated the feasibility of an automated analysis system to assist reviewers with evaluation of the general properties in the EEG background pattern. Methods Quantitative EEG methods were used to describe the following five background properties: posterior dominant rhythm frequency and reactivity, anterior-posterior gradients, presence of diffuse slow-wave activity and asymmetry. Software running the quantitative methods were given to ten experienced electroencephalographers together with 45 routine EEG recordings and computer-generated reports. Participants were asked to review the EEGs by visual analysis first, and afterwards to compare their findings with the generated reports and correct mistakes made by the system. Corrected reports were returned for comparison. Results Using a gold-standard derived from the consensus of reviewers, inter-rater agreement was calculated for all reviewers and for automated interpretation. Automated interpretation together with most participants showed high (kappa > 0.6) agreement with the gold standard. In some cases, automated analysis showed higher agreement with the gold standard than participants. When asked in a questionnaire after the study, all participants considered computer-assisted interpretation to be useful for every day use in routine reviews. Conclusions Automated interpretation methods proved to be accurate and were considered to be useful by all participants. Significance Computer-assisted interpretation of the EEG background pattern can bring consistency to reviewing and improve efficiency and inter-rater agreement.
Original languageEnglish
Article numbere85966
Pages (from-to)-
JournalPLoS ONE
Issue number1
Publication statusPublished - 2014


  • METIS-309384
  • IR-94452


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