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International Conference on Brain Informatics

BI 2020: Brain Informatics pp 163–172Cite as

Automatic Detection of Epileptic Waves in Electroencephalograms Using Bag of Visual Words and Machine Learning

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 12241)

Abstract

Epilepsy is one of the most recurrent brain disorders worldwide and mainly affects children. As a diagnostic support, the electroencephalogram is used, which is relatively easy to apply but requires a long time to analyze. Automatic EEG analysis presents difficulties both in the construction of the database and in the extracted characteristics used to build models. This article a machine learning-based methodology that uses a visual word bag of raw EEG images as input to identify images with abnormal signals. The performance introduces of the algorithms was tested using a proprietary pediatric EEG database. Accuracy greater than 95% was achieved, with calculation times less than 0.01 s per image. Therefore, the paper demonstrates the feasibility of using machine learning algorithms to directly analyze EEG images.

Keywords

  • Childhood epilepsy
  • Feature extraction and selection
  • Supervised classification
  • Visual categorization
  • Semantic categorization

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Acknowledgment

This work was funded by the Colombian Agency for Science, Technology, and Innovation - COLCIENCIAS - in call 715-2015, “Call for Research and Development Projects in Engineering” Project “NeuroMoTIC: Mobile System for Diagnostic Support of Epilepsy,” contract number FP44842-154-2016.

Author information

Authors and Affiliations

  1. Physics Department, Universidad del Cauca, Calle 5 #4-70, 190003, Popayán, Cauca, Colombia

    Marlen Sofía Muñoz, Camilo Ernesto Sarmiento Torres & Rubiel Vargas-Cañas

  2. Telematics Department, Universidad del Cauca, Calle 5 #4-70, 190003, Popayán, Cauca, Colombia

    Diego M. López & Ricardo Salazar-Cabrera

Authors
  1. Marlen Sofía Muñoz
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  2. Camilo Ernesto Sarmiento Torres
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  3. Diego M. López
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  4. Ricardo Salazar-Cabrera
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  5. Rubiel Vargas-Cañas
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Corresponding author

Correspondence to Diego M. López .

Editor information

Editors and Affiliations

  1. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  2. University of Padua, Padua, Italy

    Stefano Vassanelli

  3. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  4. Maebashi Institute of Technology, Maebashi, Japan

    Prof. Dr. Ning Zhong

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Muñoz, M.S., Torres, C.E.S., López, D.M., Salazar-Cabrera, R., Vargas-Cañas, R. (2020). Automatic Detection of Epileptic Waves in Electroencephalograms Using Bag of Visual Words and Machine Learning. In: Mahmud, M., Vassanelli, S., Kaiser, M.S., Zhong, N. (eds) Brain Informatics. BI 2020. Lecture Notes in Computer Science(), vol 12241. Springer, Cham. https://doi.org/10.1007/978-3-030-59277-6_15

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  • DOI: https://doi.org/10.1007/978-3-030-59277-6_15

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