Literature DB >> 12935113

Inability of Lyapunov exponents to predict epileptic seizures.

Ying-Cheng Lai1, Mary Ann F Harrison, Mark G Frei, Ivan Osorio.   

Abstract

It has been claimed that Lyapunov exponents computed from electroencephalogram or electrocorticogram (ECoG) time series are useful for early prediction of epileptic seizures. We show, by utilizing a paradigmatic chaotic system, that there are two major obstacles that can fundamentally hinder the predictive power of Lyapunov exponents computed from time series: finite-time statistical fluctuations and noise. A case study with an ECoG signal recorded from a patient with epilepsy is presented.

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Year:  2003        PMID: 12935113     DOI: 10.1103/PhysRevLett.91.068102

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  8 in total

1.  Complexity measures of brain wave dynamics.

Authors:  Jianbo Gao; Jing Hu; Wen-Wen Tung
Journal:  Cogn Neurodyn       Date:  2011-02-09       Impact factor: 5.082

2.  A distance-based dynamical transition analysis of time series signals and application to biological systems.

Authors:  Serkan Alagoz; Baris Baykant Alagoz
Journal:  J Biol Phys       Date:  2011-12-10       Impact factor: 1.365

3.  Detection of seizure rhythmicity by recurrences.

Authors:  Mary Ann F Harrison; Mark G Frei; Ivan Osorio
Journal:  Chaos       Date:  2008-09       Impact factor: 3.642

4.  Seizure prediction.

Authors:  J Chris Sackellares
Journal:  Epilepsy Curr       Date:  2008 May-Jun       Impact factor: 7.500

5.  An investigation of EEG dynamics in an animal model of temporal lobe epilepsy using the maximum Lyapunov exponent.

Authors:  Sandeep P Nair; Deng-Shan Shiau; Jose C Principe; Leonidas D Iasemidis; Panos M Pardalos; Wendy M Norman; Paul R Carney; Kevin M Kelly; J Chris Sackellares
Journal:  Exp Neurol       Date:  2008-11-27       Impact factor: 5.330

6.  A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction.

Authors:  Farzaneh Shayegh; Rasoul Amir Fattahi; Saeid Sadri; Karim Ansari-Asl
Journal:  J Med Signals Sens       Date:  2011-01

7.  Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis.

Authors:  Liang Huang; Xuan Ni; William L Ditto; Mark Spano; Paul R Carney; Ying-Cheng Lai
Journal:  R Soc Open Sci       Date:  2017-01-18       Impact factor: 2.963

8.  Fast monitoring of epileptic seizures using recurrence time statistics of electroencephalography.

Authors:  Jianbo Gao; Jing Hu
Journal:  Front Comput Neurosci       Date:  2013-10-01       Impact factor: 2.380

  8 in total

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