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An anomaly detection approach for dyslexia diagnosis using EEG signals

  • Autores: A. Ortiz Barragan, P. J. Lopez, Juan Luis Luque Vilaseca, Francisco Jesús Martínez Murcia Árbol académico, Diego Aquino Brítez, J.J. Ortega López
  • Localización: Understanding the Brain Function and Emotions: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019 Almería, Spain, June 3–7, 2019 Proceedings, Part I / José Manuel Ferrández Vicente (dir. congr.) Árbol académico, José Ramón Álvarez Sánchez (dir. congr.) Árbol académico, Félix de la Paz López (dir. congr.) Árbol académico, Francisco Javier Toledo Moreo (dir. congr.), Hojjat Adeli (dir. congr.), 2019, ISBN 978-3-030-19591-5, págs. 369-378
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • Developmental dyslexia (DD) is a specific difficulty in theacquisition of reading skills not related to mental age or inadequateschooling. Its prevalence is estimated between 5% and 12% of the population. Currently, biological causes and processes of DD are not well known and it is usually diagnosed by means of specifically designed tests to measure different behavioural variables involved in the reading process. Thus, the diagnosis results depend on the analysis of the test results which is a time-consuming task and prone to error. In this paper we use EEG signals to search for brain activation patterns related to DD that could result useful for differential diagnosis by an objective test. Specifically, we extract spectral features from each electrode. Moreover, the exploration of the activation levels at different brain areas constitutes an step towards the best knowledge of the brain proccesses involved in DD.


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