Abásolo, Daniel, James, Christopher and Hornero, Roberto
Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection
At 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2007).
23 - 26 Aug 2007.
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Epileptic seizures are generated by an abnormal synchronization of neurons unforeseeable for the patients. In this study we analyzed invasive electroencephalogram (EEG) recordings in patients suffering from medically intractable focal epilepsy with two non-linear methods, Approximate Entropy (ApEn) and Lempel-Ziv (LZ) complexity. ApEn and LZ complexity quantify the regularity and complexity of a time series, respectively, and are well suited to the analysis of non-stationary biomedical signals of short length. Our results show an increase in ApEn and LZ complexity values during seizures at the focal electrodes. These changes could also be seen at some extra focal electrodes. After the seizure ends, the values of both non-linear metrics return to values lower than those before the seizure. Moreover, we quantified the changes in LZ complexity, showing the complexity increase during the seizure and its notable decrease after its end. Our results suggest that these techniques are useful to detect changes due to epileptic seizures in the EEG.
Conference or Workshop Item
|Venue - Dates:
||29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2007), 2007-08-23 - 2007-08-26
||nonlinear analysis, biomedical signal classification, nonlinear dynamics
|24 August 2007||Published|
||04 Dec 2007
||16 Apr 2017 18:18
|Further Information:||Google Scholar|
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