Document Detail


Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection.
MedLine Citation:
PMID:  18002366     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Daniel Abásolo; Christopher J James; Roberto Hornero
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference     Volume:  2007     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2007  
Date Detail:
Created Date:  2007-11-16     Completed Date:  2008-04-02     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1953-6     Citation Subset:  IM    
Affiliation:
Biomedical Engineering Group, Department of Signal Theory and Communications, ETSI de Telecomunicación, University of Valladolid, Camino del Cementerio s/n, 47011, Valladolid, Spain. daniel.abasolo@tel.uva.es
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MeSH Terms
Descriptor/Qualifier:
Adult
Data Interpretation, Statistical
Diagnosis, Computer-Assisted
Electroencephalography / instrumentation*,  methods*
Electronics, Medical
Entropy
Epilepsy / diagnosis*,  pathology*
Equipment Design
Female
Humans
Male
Pattern Recognition, Automated
Pilot Projects
Software

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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