The colorful brain: Visualization of EEG background patterns

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)

Abstract

This article presents a method to transform routine clinical EEG recordings to an alternative visual domain. The method is intended to support the classic visual interpretation of the EEG background pattern and to facilitate communication about relevant EEG characteristics. In addition, it provides various quantitative features. The EEG features used in the transformation include color-coded time–frequency representations of two novel symmetry measures and a synchronization measure, based on a nearest-neighbor coherence estimate. This triplet captures three highly relevant aspects of the dynamics of the EEG background pattern, which correlate strongly with various neurologic conditions. In particular, it quantifies and visualizes the spatiotemporal distribution of the EEG power in the anterioposterior and lateral direction, and the short-distance coherence. The potential clinical use is illustrated by application of the proposed technique to various normal and abnormal EEGs, including seizure activity and the transition to sleep. The proposed transformation visualizes various essential elements of EEG background patterns. Quantitative analysis of clinical EEG recordings and transformation to alternative domains assists in the interpretation and contributes to an objective interpretation.
Original languageUndefined
Pages (from-to)63-68
JournalJournal of clinical neurophysiology
Volume25
Issue number2
DOIs
Publication statusPublished - 2008

Keywords

  • Time-frequency
  • Background pattern
  • Coherence
  • Transformation
  • Visualization
  • EEG
  • Symmetry
  • METIS-265002
  • IR-78039

Cite this

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title = "The colorful brain: Visualization of EEG background patterns",
abstract = "This article presents a method to transform routine clinical EEG recordings to an alternative visual domain. The method is intended to support the classic visual interpretation of the EEG background pattern and to facilitate communication about relevant EEG characteristics. In addition, it provides various quantitative features. The EEG features used in the transformation include color-coded time–frequency representations of two novel symmetry measures and a synchronization measure, based on a nearest-neighbor coherence estimate. This triplet captures three highly relevant aspects of the dynamics of the EEG background pattern, which correlate strongly with various neurologic conditions. In particular, it quantifies and visualizes the spatiotemporal distribution of the EEG power in the anterioposterior and lateral direction, and the short-distance coherence. The potential clinical use is illustrated by application of the proposed technique to various normal and abnormal EEGs, including seizure activity and the transition to sleep. The proposed transformation visualizes various essential elements of EEG background patterns. Quantitative analysis of clinical EEG recordings and transformation to alternative domains assists in the interpretation and contributes to an objective interpretation.",
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The colorful brain: Visualization of EEG background patterns. / van Putten, Michel Johannes Antonius Maria.

In: Journal of clinical neurophysiology, Vol. 25, No. 2, 2008, p. 63-68.

Research output: Contribution to journalArticleAcademicpeer-review

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AB - This article presents a method to transform routine clinical EEG recordings to an alternative visual domain. The method is intended to support the classic visual interpretation of the EEG background pattern and to facilitate communication about relevant EEG characteristics. In addition, it provides various quantitative features. The EEG features used in the transformation include color-coded time–frequency representations of two novel symmetry measures and a synchronization measure, based on a nearest-neighbor coherence estimate. This triplet captures three highly relevant aspects of the dynamics of the EEG background pattern, which correlate strongly with various neurologic conditions. In particular, it quantifies and visualizes the spatiotemporal distribution of the EEG power in the anterioposterior and lateral direction, and the short-distance coherence. The potential clinical use is illustrated by application of the proposed technique to various normal and abnormal EEGs, including seizure activity and the transition to sleep. The proposed transformation visualizes various essential elements of EEG background patterns. Quantitative analysis of clinical EEG recordings and transformation to alternative domains assists in the interpretation and contributes to an objective interpretation.

KW - Time-frequency

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KW - Symmetry

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KW - IR-78039

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