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

Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection
Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection
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.
nonlinear analysis, biomedical signal classification, nonlinear dynamics
1953-1956
Abásolo, Daniel
e3dcf2ea-c0a5-409c-b0b9-6902a827d331
James, Christopher
c181ef38-6aec-4e52-8c57-48899e3534b5
Hornero, Roberto
52474f4c-c276-4cee-92db-dfb4910b0800
Abásolo, Daniel
e3dcf2ea-c0a5-409c-b0b9-6902a827d331
James, Christopher
c181ef38-6aec-4e52-8c57-48899e3534b5
Hornero, Roberto
52474f4c-c276-4cee-92db-dfb4910b0800

Abásolo, Daniel, James, Christopher and Hornero, Roberto (2007) Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2007), Lyon, France. 22 - 25 Aug 2007. pp. 1953-1956 .

Record type: Conference or Workshop Item (Paper)

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.

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More information

Published date: 24 August 2007
Venue - Dates: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2007), Lyon, France, 2007-08-22 - 2007-08-25
Keywords: nonlinear analysis, biomedical signal classification, nonlinear dynamics

Identifiers

Local EPrints ID: 49443
URI: http://eprints.soton.ac.uk/id/eprint/49443
PURE UUID: e326e7f4-ccb8-4e01-aeb5-98bf2222858f

Catalogue record

Date deposited: 04 Dec 2007
Last modified: 08 Jan 2022 07:03

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Contributors

Author: Daniel Abásolo
Author: Christopher James
Author: Roberto Hornero

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