Abstract:
New approach to investigation of electroencephalogram (EEG) patterns over different time spans is proposed based on permutation entropy (PE) measure. PE for large time la...Show MoreMetadata
Abstract:
New approach to investigation of electroencephalogram (EEG) patterns over different time spans is proposed based on permutation entropy (PE) measure. PE for large time lags (1-100 samples) and orders from 2 to 8 was calculated for EEG signals of three types: EEG from healthy subject, EEG containing high-magnitude bursts and EEG with epileptiform complexes. PE value saturation phenomena is revealed for large time lags (approximately 10 or 30 samples for different EEG types) and for whole range of orders used in this study. This effect might be due to the inherent EEG property, namely that the samples in each EEG pattern are spaced too far from each other and they are like samples from some arbitrary stochastic process.
Published in: 2013 IEEE XXXIII International Scientific Conference Electronics and Nanotechnology (ELNANO)
Date of Conference: 16-19 April 2013
Date Added to IEEE Xplore: 08 July 2013
ISBN Information: