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

被引:238
作者
Cassani, Raymundo [1 ]
Estarellas, Mar [1 ,2 ]
San-Martin, Rodrigo [3 ]
Fraga, Francisco J. [4 ]
Falk, Tiago H. [1 ]
机构
[1] Univ Quebec, EMT, INRS, Montreal, PQ, Canada
[2] Imperial Coll London, Dept Bioengn, London, England
[3] Univ Fed ABC, Ctr Math Computat & Cognit, Sao Bernardo Do Campo, Brazil
[4] Univ Fed ABC, Engn Modeling & Appl Social Sci Ctr, Sao Bernardo Do Campo, Brazil
基金
巴西圣保罗研究基金会;
关键词
MILD COGNITIVE IMPAIRMENT; FREQUENCY POWER RATIO; MINI-MENTAL-STATE; NATIONAL INSTITUTE; ASSOCIATION WORKGROUPS; SPECTRAL-ANALYSIS; QUANTITATIVE EEG; DIFFERENTIAL-DIAGNOSIS; NEURAL SYNCHRONIZATION; CORTICAL CONNECTIVITY;
D O I
10.1155/2018/5174815
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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.
引用
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页数:26
相关论文
共 189 条
[91]   Extracting Salient Features for EEG-based Diagnosis of Alzheimer's Disease Using Support Vector Machine Classifier [J].
Kulkarni, N. N. ;
Bairagi, V. K. .
IETE JOURNAL OF RESEARCH, 2017, 63 (01) :11-22
[92]   Innovative diagnostic tools for early detection of Alzheimer's disease [J].
Laske, Christoph ;
Sohrabi, Hamid R. ;
Frost, Shaun M. ;
Lopez-de-Ipina, Karmele ;
Garrard, Peter ;
Buscema, Massimo ;
Dauwels, Justin ;
Soekadar, Surjo R. ;
Mueller, Stephan ;
Linnemann, Christoph ;
Bridenbaugh, Stephanie A. ;
Kanagasingam, Yogesan ;
Martins, Ralph N. ;
O'Bryant, Sid E. .
ALZHEIMERS & DEMENTIA, 2015, 11 (05) :561-578
[93]   Multiway array decomposition analysis of EEGs in Alzheimer's disease [J].
Latchoumane, Charles-Francois V. ;
Vialatte, Francois-Benois ;
Sole-Casals, Jordi ;
Maurice, Monique ;
Wimalaratna, Sunil R. ;
Hudson, Nigel ;
Jeong, Jaeseung ;
Cichocki, Andrzej .
JOURNAL OF NEUROSCIENCE METHODS, 2012, 207 (01) :41-50
[94]   Global synchronization index as a biological correlate of cognitive decline in Alzheimer's disease [J].
Lee, Seung-Hwan ;
Park, Young-Min ;
Kim, Do-Won ;
Im, Chang-Hwan .
NEUROSCIENCE RESEARCH, 2010, 66 (04) :333-339
[95]  
Liberati A, 2009, ANN INTERN MED, V151, pW65, DOI [10.7326/0003-4819-151-4-200908180-00136, 10.1371/journal.pmed.1000100]
[96]   Multiple characteristics analysis of Alzheimer's electroencephalogram by power spectral density and Lempel-Ziv complexity [J].
Liu, Xiaokun ;
Zhang, Chunlai ;
Ji, Zheng ;
Ma, Yi ;
Shang, Xiaoming ;
Zhang, Qi ;
Zheng, Wencheng ;
Li, Xia ;
Gao, Jun ;
Wang, Ruofan ;
Wang, Jiang ;
Yu, Haitao .
COGNITIVE NEURODYNAMICS, 2016, 10 (02) :121-133
[97]   Neurophysiological Assessment of Alzheimer's Disease Individuals by a Single Electroencephalographic Marker [J].
Lizio, Roberta ;
Del Percio, Claudio ;
Marzano, Nicola ;
Soricelli, Andrea ;
Yener, Gorsev G. ;
Basar, Erol ;
Mundi, Ciro ;
De Rosa, Salvatore ;
Triggiani, Antonio Ivano ;
Ferri, Raffaele ;
Arnaldi, Dario ;
Nobili, Flavio Mariano ;
Cordone, Susanna ;
Lopez, Susanna ;
Carducci, Filippo ;
Santi, Giulia ;
Gesualdo, Loreto ;
Rossini, Paolo M. ;
Cavedo, Enrica ;
Mauri, Margherita ;
Frisoni, Giovanni B. ;
Babiloni, Claudio .
JOURNAL OF ALZHEIMERS DISEASE, 2016, 49 (01) :159-177
[98]   Electroencephalogram Global Field Synchronization Analysis: A New Method for Assessing the Progress of Cognitive Decline in Alzheimer's disease [J].
Ma, Chi-Cheng ;
Liu, Ai-Jun ;
Liu, Ai-Hua ;
Zhou, Xue-Ying ;
Zhou, Sheng-Nian .
CLINICAL EEG AND NEUROSCIENCE, 2014, 45 (02) :98-103
[99]   Electroencephalographic markers in dementia [J].
Malek, N. ;
Baker, M. R. ;
Mann, C. ;
Greene, J. .
ACTA NEUROLOGICA SCANDINAVICA, 2017, 135 (04) :388-393
[100]   A Permutation Disalignment Index-Based Complex Network Approach to Evaluate Longitudinal Changes in Brain-Electrical Connectivity [J].
Mammone, Nadia ;
De Salvo, Simona ;
Ieracitano, Cosimo ;
Marino, Silvia ;
Marra, Angela ;
Corallo, Francesco ;
Morabito, Francesco Carlo .
ENTROPY, 2017, 19 (10)