Performance Evaluation and Fusion of Methods for Early Detection of Alzheimer Disease

Hamadicharef, Brahim; Guan, Cuntai; Ifeachor, Emmanuel; Hudson, N.R.; Wimalaratna, Sunil

doi:10.1109/bmei.2008.196

Cited by 7 publications

(13 citation statements)

References 33 publications

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“…Hamadicharef et al [84] used 19-recording electrodes plus ground and system reference for EEG recording for dementia patients; these electrodes were located according to 10–20 electrode system as follows: Fp1, Fp2, F7, F3, Fz, F4, F8, A1, T3, C3, Cz, C4, T4, A2, T5, P3, Pz, P4, T6, O1, and O2 [85]. …”

Section: Function Of Eeg In the Early Detection And Classificationmentioning

confidence: 99%

“…For fruitful clinical application, the EEG of dementia patients has been recorded in a specialized clinical unit state with the 10–20 system of the international federation, which is adopted by the American EEG Society, while resting with eyes comfortably closed, as shown in Figure 7 . Hamadicharef et al [ 84 ] used 19-recording electrodes plus ground and system reference for EEG recording for dementia patients; these electrodes were located according to 10–20 electrode system as follows: Fp1, Fp2, F7, F3, Fz, F4, F8, A1, T3, C3, Cz, C4, T4, A2, T5, P3, Pz, P4, T6, O1, and O2 [ 85 ].…”

Section: Function Of Eeg In the Early Detection And Classificationmentioning

confidence: 99%

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Role of EEG as Biomarker in the Early Detection and Classification of Dementia

Al-Qazzaz

Ali

Ahmad

et al. 2014

The Scientific World Journal

163

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The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.

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Section: Function Of Eeg In the Early Detection And Classificationmentioning

confidence: 99%

Section: Function Of Eeg In the Early Detection And Classificationmentioning

confidence: 99%

Role of EEG as Biomarker in the Early Detection and Classification of Dementia

Al-Qazzaz

Ali

Ahmad

et al. 2014

The Scientific World Journal

163

View full text Add to dashboard Cite

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“…In this study, we reviewed an important class of complexity measures, information-theoretic methods, which offers a potentially powerful approach for quantifying changes in the EEG due to AD [59]. Information-theoretic methods have emerged as a potentially useful complexity-based approach to derive robust EEG biomarkers of AD [50,59,60,65,110,111]. They are attractive due to the potential natural connection between biomarkers based on information theory and brain changes induced by AD [59].…”

Section: Discussionmentioning

confidence: 99%

“…In particular, TsEn approach has been shown to be one of the most promising information-theoretic methods for quantifying EEG complexity [34,59,60,64,65]. It has also been shown to be a reliable analysis tool to use with working memory tasks.…”

Section: Reduction In Eeg Complexitymentioning

confidence: 99%

“…It has also been shown to be a reliable analysis tool to use with working memory tasks. Its capacity for rapid computation may serve as the basis for real-time decision support tools for diagnosing AD [34,59,[65][66][67]. Sneddon et al [68] analyzed EEG TsEn and found that it was capable of detecting mild dementia due to AD with 88% for sensitivity and 94% for specificity.…”

Section: Reduction In Eeg Complexitymentioning

confidence: 99%

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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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The Electroencephalogram as a Biomarker Based on Signal Processing Using Nonlinear Techniques to Detect Dementia

Guerra

Lanzarini

Sanchez

2018

Smart Innovation, Systems and Technologies

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Dementia being a syndrome caused by a brain disease of a chronic or progressive nature, in which the irreversible loss of intellectual abilities, learning, expressions arises; including memory, thinking, orientation, understanding and adequate communication, of organizing daily life and of leading a family, work and autonomous social life; leads to a state of total dependence; therefore, its early detection and classification is of vital importance in order to serve as clinical support for physicians in the personalization of treatment programs. The use of the electroencephalogram as a tool for obtaining information on the detection of changes in brain activities. This article reviews the types of cognitive spectrum dementia, biomarkers for the detection of dementia, analysis of mental states based on electromagnetic oscillations, signal processing given by the electroencephalogram, review of processing techniques, results obtained where it is proposed the mathematical model about neural networks, discussion and finally the conclusions.

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Performance Evaluation and Fusion of Methods for Early Detection of Alzheimer Disease

Abstract: Abstract

Cited by 7 publications

References 33 publications

Role of EEG as Biomarker in the Early Detection and Classification of Dementia

Role of EEG as Biomarker in the Early Detection and Classification of Dementia

Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease

The Electroencephalogram as a Biomarker Based on Signal Processing Using Nonlinear Techniques to Detect Dementia

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