Investigation of Alzheimer’s Disease EEG Frequency Components with Lempel-Ziv Complexity

Simons, Samantha; Abásolo, Daniel; Hughes, Michael

doi:10.1007/978-3-319-11128-5_12

Cited by 7 publications

(6 citation statements)

References 14 publications

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“…The most characteristic feature caused by AD is the reduction in EEG complexity [33-35, 37, 38, 40, 41] compared to normal subjects. This is consistent with other studies [35,38,43,46,56,58,62,64,80,97,98] and shows that EEG complexity measures are potentially a good biomarker for detecting AD. Unlike previous studies, we found that the complexity measures derived from the EEG frequency bands (i.e., delta, theta, alpha, beta, and gamma) provide significantly better performance in detecting AD than the complexity measures derived from whole EEG records.…”

Section: Discussionsupporting

confidence: 93%

Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease

et al. 2018

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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%.

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Section: Discussionsupporting

confidence: 93%

Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease

et al. 2018

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“…Given the association of EEG activities (e.g., alpha, delta activities) with AD, Al-nuaimi et al [49] they proved that the derivation of EEG complexity based on EEG activities should lead to enhanced performance. This reduction can be measured using different methods e.g., Tsallis entropy (TsEn) [34,59,60], Higuchi Fractal Dimension (HFD) [61], and Lempel Ziv Complexity (LZC) [41,47]. Consequently, EEG complexity can potentially be a good biomarker for AD diagnosis [37] as AD patients exhibit a significant reduction in EEG complexity [37-39, 48, 55, 62, 63].…”

Section: Reduction In Eeg Complexitymentioning

confidence: 99%

“…While biomarkers derived from the EEG complexity analysis are based on non-linear methods (e.g. entropy methods, fractal dimension, and Lempel-Ziv complexity) [44][45][46][47].This chapter describes research into the development of EEG biomarkers that detect AD based on analysis of changes in the EEG. These changes can be quantified as a biomarker of AD.…”

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confidence: 99%

Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease

Al-nuaimi¹

2020

Neuroimaging - Neurobiology, Multimodal and Network Applications

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Alzheimer's disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have not obtained a formal early diagnosis, and this may provide them with a chance to access suitable healthcare facilities. An early diagnosis biomarker capable of measuring brain cell degeneration due to AD would be valuable. Potentially, electroencephalogram (EEG) can play a valuable role in the early diagnosis of AD. EEG is noninvasive and low cost, and provides valuable information about brain dynamics in AD. Thus, EEG-based biomarkers may be used as a first-line decisionsupport tool in AD diagnosis and could complement other AD biomarkers.Keywords: EEG biomarkers, AD biomarkers, slowing of EEG, decrease in EEG coherence, reduction in EEG complexity, detection of Alzheimer's disease Neuroimaging -Neurobiology, Multimodal and Network Applications 2 an enormous financial. However, many dementia sufferers are not diagnosed early [7,8]. It is estimated that up to 50% of individuals with dementia may not have been diagnosed formally [8, 9]. In 2011, 28 million people out of 36 million people with dementia were not diagnosed worldwide [10].Degeneration of brain cells due to AD begins many years before clinical manifestations become noticeable [5,[11][12][13][14][15]. Early diagnosis of AD will help to the development of efficient treatments that could mitigate, stop, or prevent significant cognitive impairment [14, 16, 17]. Early diagnosis of AD may also be valuable in detecting patients with dementia who have not obtained a formal early diagnosis, and this may provide them with a chance to access suitable healthcare facilities [18][19][20].An early diagnosis biomarker that can measure brain cell degeneration due to AD would be valuable [2,[21][22][23]. But this may involve dealing with an extremely large number of individuals, as up to 50% of individuals with dementia may not have been diagnosed formally. Therefore, Simple, non-invasive, low-cost and reliable biomarkers are necessary for early diagnosis that can be accessed in clinical practice [5,24,25]. Recent guidelines support the use of biomarkers for biochemical and neuroimaging to promote AD diagnosis. AD testing of cerebral spinal fluid (CSF) is not commonly used in clinical practice as it involves lumbar puncture, an invasive procedure [2,26,27]. Neuroimaging is expensive, accessible only in specialized centers [28], and may ...

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“…A CLZ é uma medida de complexidade que tem sido usada para analisar os sinais de EEG em pacientes com a Doença de Alzheimer, Transtorno do Déficit de Atenção com Hiperatividade (TDAH), medir o aprofundamento de anestesia, epilepsia dentre outras condições (LEE et al, 2014;SIMONS et al,2015;IBÁÑEZ-MOLINA et al, 2015).…”

Section: Conclusõesunclassified