Detecting complexity abnormalities in dyslexia measuring approximate entropy of electroencephalographic signals

@article{Andreadis2009DetectingCA,
  title={Detecting complexity abnormalities in dyslexia measuring approximate entropy of electroencephalographic signals},
  author={Ioannis I. Andreadis and Giorgos A. Giannakakis and Charalambos C. Papageorgiou and Konstantina S. Nikita},
  journal={2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  year={2009},
  pages={6292-6295}
}
Dyslexia constitutes a specific reading disability, a condition characterized by severe difficulty in the mastery of reading despite normal intelligence or adequate education. Electroencephalogram (EEG) signal may be able to play an important role in the diagnosis of dyslexia. The Approximate Entropy (ApEn) is a recently formulated statistical parameter used to quantify the regularity of a time series data of physiological signals. In this paper, we initially estimated the ApEn values in… CONTINUE READING

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