Electroencephalography-driven approach to prodromal Alzheimer&amp;#39;s disease diagnosis: from biomarker integration to network-level comprehension

Moretti, Davide Vito

doi:10.2147/cia.s103313

Cited by 13 publications

(13 citation statements)

References 121 publications

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“…EOG and ECG are helpful as reference for cleaning the EEG signals as ocular and heart activity artifacts will be easier to detect and clean. Forty-one studies mention the registration of EOG signals in their studies [ 42 , 66 , 81 , 82 , 89 , 103 , 115 , 130 , 131 , 133 , 136 – 139 , 141 , 143 – 147 , 150 , 152 – 160 , 162 , 164 – 166 , 169 , 170 , 172 , 174 – 177 ] and twelve mention the use of ECG [ 38 , 42 , 131 , 144 – 146 , 161 – 163 , 168 , 172 , 175 ].…”

Section: Resultsmentioning

confidence: 99%

Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

et al. 2018

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Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databases were analyzed. A total of 112 journal articles published from January 2010 to February 2018 were meticulously reviewed, and relevant aspects of these papers were compared across articles to provide a general overview of the research on this noninvasive AD diagnosis technique. Finally, recommendations for future studies with resting-state EEG were presented to improve and facilitate the knowledge transfer among research groups.

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Section: Resultsmentioning

confidence: 99%

Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

et al. 2018

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“…Potentially, EEG can play a vital role in the early detection of AD [5,6,7,11,12]. Damage to nerve cells/pathways in the brain due to AD causes changes in the information-processing activity of the brain.…”

Section: Introductionmentioning

confidence: 99%

Higuchi fractal dimension of the electroencephalogram as a biomarker for early detection of Alzheimer's disease

Al-nuaimi

Jammeh

Sun

et al. 2017

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual slowing of brain activity caused by AD starts from the back of the brain and spreads out towards other parts. Consequently, determining the brain regions that are first affected by AD may be useful in its early diagnosis. Higuchi fractal dimension (HFD) has characteristics which make it suited to capturing region-specific neural changes due to AD. The aim of this study is to investigate the potential of HFD of the EEG as a biomarker which is associated with the brain region first affected by AD. Mean HFD value was calculated for all channels of EEG signals recorded from 52 subjects (20-AD and 32-normal). Then, p-values were calculated between the two groups (AD and normal) to detect EEG channels that have a significant association with AD. k-nearest neighbor (KNN) algorithm was used to compute the distance between AD patients and normal subjects in the classification. Our results show that AD patients have significantly lower HFD values in the parietal areas. HFD values for channels in these areas were used to discriminate between AD and normal subjects with a sensitivity and specificity values of 100% and 80%, respectively.

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“…Slowing may therefore be quantified as a biomarker of AD [11, 37,83]. It can be measured in several ways such as changes in EEG amplitude (ΔEEG A ), zero-crossing intervals (ZCI) [11], and changes in the power spectrum (ΔPS) of the EEG signal [11, 32,33,37,39,[84][85][86][87][88][89][90][91]. Al-nuaimi et al [5] quantified slowing in EEG by measuring the ΔEEG A .…”

Section: Slowing Of Eegmentioning

confidence: 99%

“…This increase was related to a decline in memory and can therefore be used to identify MCI patients in a cohort of normal people [36]. Numerous studies have shown that power changes in the EEG frequency bands are promising markers of AD [84][85][86][87][88][89][90][91].…”

Section: Slowing Of Eegmentioning

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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Electroencephalography-driven approach to prodromal Alzheimer's disease diagnosis: from biomarker integration to network-level comprehension

Cited by 13 publications

References 121 publications

Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

Higuchi fractal dimension of the electroencephalogram as a biomarker for early detection of Alzheimer's disease

Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease

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