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Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection.

Abásolo, D, James, CJ and Hornero, R (2007) Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection. In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2007-08-22 - 2007-08-26, United States.

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Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Additional Information:

Copyright 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Uncontrolled Keywords: Adult, Data Interpretation, Statistical, Diagnosis, Computer-Assisted, Electroencephalography, Electronics, Medical, Entropy, Epilepsy, Equipment Design, Female, Humans, Male, Pattern Recognition, Automated, Pilot Projects, Software
Divisions: Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Depositing User: Symplectic Elements
Date Deposited: 02 Oct 2012 15:34
Last Modified: 23 Sep 2013 19:36
URI: http://epubs.surrey.ac.uk/id/eprint/713547

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