Spectral entropy of dyslexic erp signal by means of adaptive optimal kernel

  • Authors:

  • Giorgos A. Giannakakis;Nikolaos N. Tsiaparas;Charalabos Papageorgiou;Konstantina S. Nikita

  • Affiliations:

  • National Technical University of Athens, Biomedical Simulations and Imaging Laboratory, Athens, Greece;National Technical University of Athens, Biomedical Simulations and Imaging Laboratory, Athens, Greece;University of Athens, Department of Psychiatry, Eginition Hospital, Athens, Greece;National Technical University of Athens, Biomedical Simulations and Imaging Laboratory, Athens, Greece

  • Venue:
  • DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
  • Year:
  • 2009

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Abstract

In this paper, subband spectral entropy (SSE) and its relative. form was used for the analysis of rest electroencephalogram (EEG) and Event Related Potentials (ERP). The recorded signals were taken from control children and children with dyslexia. Adaptive-Optimal-Kernel (AOK) time-frequency representation was used to produce high resolution spectrogram. Then, SSE and relative subband spectral entropy (RSSE) were calculated. The entropic patterns of both controls and dyslexics were investigated showing differences in specific electrode recordings.