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.
Original language | English |
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Article number | 068102 |
Number of pages | 4 |
Journal | Physical Review Letters |
Volume | 91 |
Issue number | 6 |
DOIs | |
Publication status | Published - 8 Aug 2003 |
Keywords
- brain electrical activity
- time-series analysis
- preictal transition
- scalp egg
- dimension
- dynamics
- chaos