Implementation of ECoG Signal Energy, Entropy and Fractal Dimension for Spike Detection

Localization of the epileptogenic zone (EZ) is very important for patients undergoing presurgical evaluation for resective epilepsy surgery. The detection of epileptiform spikes is of major importance for identifying the epileptogenic zone. The zone of cortex with interictal spikes is usually revealed intraoperatively, during acute electrocorticography (ECoG). The ECoG recordings cannot be completely visually reviewed, by a specialist, in a reasonable amount of time. So, computer algorithms for the automatic detection of spikes are very desirable. The article contains a proposal of spike detection algorithm, based on three ECoG signal parameters: signal energy, entropy and fractal dimension. The sensitivity of spike detection was 0.83, the specificity was 0.98 and the precision – 0.91.

• Publication year

  2018

• Venue

  IEEE International Symposium on Medical Measurements and Applications

• Publication date

  2018-06-01

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1109/MeMeA.2018.8438783
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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