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Volume Conduction Effects on Bivariate Lempel-Ziv Complexity of Alzheimer's Disease Electroencephalograms

Overview of attention for article published in Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), January 2015
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Article details
Title
Volume Conduction Effects on Bivariate Lempel-Ziv Complexity of Alzheimer's Disease Electroencephalograms
Published in
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), January 2015
DOI 10.1109/embc.2015.7320105
Pubmed ID
Authors
Abstract

The spurious increase in coherence of electroencephalogram (EEG) signals between distant electrode points has long been understood to be due to volume conduction of the EEG signal. Reducing the volume conduction components of EEG recordings in pre-processing attenuates this. However, the effect of volume conduction on non-linear signal processing of EEG signals is yet to be fully described. This pilot study aimed to investigate the impact of volume conduction on results calculated with a distance based, bivariate form of Lempel-Ziv Complexity (dLZC) by analyzing EEG signals from Alzheimer's disease (AD) patients and healthy age-matched controls with and without pre-processing with Current Source Density (CSD) transformation. Spurious statistically significant differences between AD patients and control's EEG signals seen without CSD pre-processing were not seen with CSD volume conduction mitigation. There was, however, overlap in the region of electrodes which were seen to hold this statistically significant information. These results show that, while previously published findings are still valid, volume conduction mitigation is required to ensure non-linear signal processing methods identify changes in signals only due to the purely local signal alone.

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The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 4 27%
Student > Bachelor 3 20%
Student > Master 3 20%
Lecturer > Senior Lecturer 1 7%
Other 1 7%
Other 1 7%
Unknown 2 13%
Readers by discipline
Readers by discipline Count As %
Psychology 3 20%
Neuroscience 3 20%
Medicine and Dentistry 2 13%
Engineering 2 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Other 2 13%
Unknown 2 13%