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Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901663/ https://www.ncbi.nlm.nih.gov/pubmed/24475064 http://dx.doi.org/10.1371/journal.pone.0085966 |
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author | Lodder, Shaun S. Askamp, Jessica van Putten, Michel J. A. M. |
author_facet | Lodder, Shaun S. Askamp, Jessica van Putten, Michel J. A. M. |
author_sort | Lodder, Shaun S. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3901663 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39016632014-01-28 Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation Lodder, Shaun S. Askamp, Jessica van Putten, Michel J. A. M. PLoS One Research Article 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. Public Library of Science 2014-01-24 /pmc/articles/PMC3901663/ /pubmed/24475064 http://dx.doi.org/10.1371/journal.pone.0085966 Text en © 2014 Lodder et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Lodder, Shaun S. Askamp, Jessica van Putten, Michel J. A. M. Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation |
title | Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation |
title_full | Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation |
title_fullStr | Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation |
title_full_unstemmed | Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation |
title_short | Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation |
title_sort | computer-assisted interpretation of the eeg background pattern: a clinical evaluation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901663/ https://www.ncbi.nlm.nih.gov/pubmed/24475064 http://dx.doi.org/10.1371/journal.pone.0085966 |
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