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Automatic Detection of Epileptic Spike in EEGs of Children Using Matched Filter

  • Maritza Mera
  • Diego M. López
  • Rubiel Vargas
  • María Miño
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11309)

Abstract

The Electroencephalogram (EEG) is one of the most used tools for diagnosing Epilepsy. Analyzing EEG, neurologists can identify alterations in brain activity associated with Epilepsy. However, this task is not always easy to perform, because of the duration of the EEGs or the subjectivity of the specialist in detecting alterations. Aim: To present an epileptic spike detector based on matched filter for supporting diagnosis of Epilepsy through a tool able to automatically detect spikes in EEG of children. Results: The results of the evaluation showed that the developed detector achieved a sensitivity of 89.28% which is within the range of what has been reported in the literature (82.68% and 94.4%), and a specificity of 99.96%, the later improving the specificity of the best reviewed work. Conclusions: Considering the results obtained in the evaluation, the solution becomes an alternative to support the automatic identification of epileptic spikes by neurologists.

Keywords

Matched filter Spike detection Epilepsy Seizure 

Notes

Acknowledgements

The work is funded by a grant from the Colombian Agency for Science, Technology, and Innovation Colciencias – under Calls 715-2015, project: “NeuroMoTIC: Sistema móvil para el Apoyo Diagnóstico de la Epilepsia”, Contract number FP44842-154-2016, and Call 647- 2015.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Telematics DepartmentUniversity of CaucaPopayánColombia
  2. 2.Physics DepartmentUniversity of CaucaPopayánColombia
  3. 3.Pediatrics DepartmentUniversity of CaucaPopayánColombia

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