Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease
Joint Authors
Sun, Lingfen
Al-Nuaimi, Ali H. Husseen
Jammeh, Emmanuel
Ifeachor, Emmanuel
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-13
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Alzheimer’s disease (AD) is a progressive disorder that affects cognitive brain functions and starts many years before its clinical manifestations.
A biomarker that provides a quantitative measure of changes in the brain due to AD in the early stages would be useful for early diagnosis of AD, but this would involve dealing with large numbers of people because up to 50% of dementia sufferers do not receive formal diagnosis.
Thus, there is a need for accurate, low-cost, and easy to use biomarkers that could be used to detect AD in its early stages.
Potentially, electroencephalogram (EEG) based biomarkers can play a vital role in early diagnosis of AD as they can fulfill these needs.
This is a cross-sectional study that aims to demonstrate the usefulness of EEG complexity measures in early AD diagnosis.
We have focused on the three complexity methods which have shown the greatest promise in the detection of AD, Tsallis entropy (TsEn), Higuchi Fractal Dimension (HFD), and Lempel-Ziv complexity (LZC) methods.
Unlike previous approaches, in this study, the complexity measures are derived from EEG frequency bands (instead of the entire EEG) as EEG activities have significant association with AD and this has led to enhanced performance.
The results show that AD patients have significantly lower TsEn, HFD, and LZC values for specific EEG frequency bands and for specific EEG channels and that this information can be used to detect AD with a sensitivity and specificity of more than 90%.
American Psychological Association (APA)
Al-Nuaimi, Ali H. Husseen& Jammeh, Emmanuel& Sun, Lingfen& Ifeachor, Emmanuel. 2018. Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease. Complexity،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1136392
Modern Language Association (MLA)
Al-Nuaimi, Ali H. Husseen…[et al.]. Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease. Complexity No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1136392
American Medical Association (AMA)
Al-Nuaimi, Ali H. Husseen& Jammeh, Emmanuel& Sun, Lingfen& Ifeachor, Emmanuel. Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease. Complexity. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1136392
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136392