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Authors: Samantha Simons and Daniel Abásolo

Affiliation: University of Surrey, United Kingdom

ISBN: 978-989-758-011-6

Keyword(s): Alzheimer’s Disease, Electroencephalogram, Non-Linear Analysis, Permutation Entropy.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics

Abstract: This pilot study applied Permutation Entropy (PE), a non-linear symbolic measure, and a novel modification (modPE), to investigate the regularity of electroencephalogram (EEG) signals from 11 Alzheimer’s disease (AD) patients and 11 age-matched controls given input parameters n (embedding vector), τ (coarse graining) and slide (difference between the start of two concurrent embedding vectors). PE discriminated better than modPE with controls showing reduced regularity over AD patients. Increasing τ identified the greatest differences between EEG signals. Longer embedding vectors were also more able to identify differences. The greatest difference between groups was at Fp1 with n,τ,slide = 3,10,1 (p=0.0112 Kruskal Wallis with Bonferroni). Subject and epoch based leave-one-out cross validation was carried out with thresholding from Receiver Operating Characteristic Curves. The greatest ability to correctly identify AD patients and controls were 81.82% (Fp2 n,τ,slide = 7,4,4, PE an d modPE, F7 n,τ,slide = 3,10,1, PE and modPE) and 90.91% (Fp1 n,τ,slide = 3,10,1, PE and modPE), respectively. The maximum accuracy (both groups correctly identified) was 81.82% seen at many electrode and input combinations. All are with subject based analysis. This suggests that PE can identify changes in EEG signals in AD, given appropriate variables. However, modPE makes little improvement over PE. (More)

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Paper citation in several formats:
Simons, S. and Abásolo, D. (2014). Permutation Entropy of the Electroencephalogram Background Activity in Alzheimer’s Disease - Investigation into the Incidence of Repeated Values.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014) ISBN 978-989-758-011-6, pages 97-103. DOI: 10.5220/0004721000970103

@conference{biosignals14,
author={Samantha Simons. and Daniel Abásolo.},
title={Permutation Entropy of the Electroencephalogram Background Activity in Alzheimer’s Disease - Investigation into the Incidence of Repeated Values},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)},
year={2014},
pages={97-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004721000970103},
isbn={978-989-758-011-6},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)
TI - Permutation Entropy of the Electroencephalogram Background Activity in Alzheimer’s Disease - Investigation into the Incidence of Repeated Values
SN - 978-989-758-011-6
AU - Simons, S.
AU - Abásolo, D.
PY - 2014
SP - 97
EP - 103
DO - 10.5220/0004721000970103

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