Validity of the Quantitative EEG Statistical Pattern Recognition Method in Diagnosing Alzheimer's Disease

被引:22
|
作者
Ommundsen, Nina [1 ]
Engedal, Knut [1 ,2 ]
Oksengard, Anne Rita [1 ,3 ,4 ,5 ]
机构
[1] Ullevaal Univ Hosp, Dept Geriatr Med, NO-0424 Oslo, Norway
[2] Ullevaal Univ Hosp, Norwegian Ctr Ageing & Hlth Res Educ & Serv Dev, NO-0424 Oslo, Norway
[3] Memory Clin, Dept Geriatr, Asker, Norway
[4] Baerum Hosp, Rud, Norway
[5] Karolinska Inst, NVS Dept, Sect Clin Geriatr, Karolinska Univ Hosp, Stockholm, Sweden
关键词
Alzheimer's disease; Dementia; Diagnostics; Electroencephalography; Mild cognitive impairment; Validate; MILD COGNITIVE IMPAIRMENT; RESTING EEG; DEMENTIA; POPULATION; ACCURACY;
D O I
10.1159/000324878
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Aims: To evaluate the use of quantitative EEG (qEEG) statistical pattern recognition in diagnosing Alzheimer's disease (AD). Methods: qEEG was performed on 104 patients referred to a memory clinic. The qEEG results were compared to the clinical diagnosis made without access to the EEG results. Results: Of 30 patients with a clinical diagnosis of AD, 22 were test positive. Of the 74 patients without AD, 34 were test negative. The qEEG result was found to correlate with atrophy of the medial temporal lobe demonstrated on cerebral MRI (p = 0.002) and with scores on neuropsychological tests. Conclusion: The qEEG was poor at diagnosing AD, as it produced many false-positive results. Copyright (C) 2011 S. Karger AG, Basel
引用
收藏
页码:195 / 201
页数:7
相关论文
共 50 条
  • [41] EEG coherence in Alzheimer's disease
    Locatelli, T
    Cursi, M
    Liberati, D
    Franceschi, M
    Comi, G
    ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1998, 106 (03): : 229 - 237
  • [42] EEG in the diagnostics of Alzheimer's disease
    Waser, M.
    Deistler, M.
    Garn, H.
    Benke, T.
    Dal-Bianco, P.
    Ransmayr, G.
    Grossegger, D.
    Schmidt, R.
    STATISTICAL PAPERS, 2013, 54 (04) : 1095 - 1107
  • [43] The validity of psychosis in Alzheimer's disease
    Schneider, LS
    Kershaw, P
    NEUROLOGY, 2001, 56 (08) : A175 - A176
  • [44] Brain image feature recognition method for Alzheimer’s disease
    Xiaoying He
    Li Chen
    Xiaogang Li
    Hua Fu
    Cluster Computing, 2019, 22 : 8109 - 8117
  • [45] Progress on early diagnosing Alzheimer's disease
    Chen, Yixin
    Al-Nusaif, Murad
    Li, Song
    Tan, Xiang
    Yang, Huijia
    Cai, Huaibin
    Le, Weidong
    FRONTIERS OF MEDICINE, 2024, 18 (03) : 446 - 464
  • [46] New Methods for Diagnosing Alzheimer's Disease
    不详
    WIENER KLINISCHE WOCHENSCHRIFT, 2024, 136 (21-22) : 642 - 642
  • [47] Early Detection of Alzheimer's Disease through Analysis of EEG Responses to Word Recognition
    Jang, Hanbyul
    Kim, Seul-Kee
    Ha, Jihyeon
    Kim, Laehyun
    2024 12TH INTERNATIONAL WINTER CONFERENCE ON BRAIN-COMPUTER INTERFACE, BCI 2024, 2024,
  • [48] A longitudinal quantitative EEG study of Alzheimer's disease:: Relation to apolipoprotein E polymorphism
    Lehtovirta, M
    Partanen, J
    Könönen, M
    Hiltunen, J
    Helisalmi, S
    Hartikainen, P
    Riekkinen, P
    Soininen, H
    DEMENTIA AND GERIATRIC COGNITIVE DISORDERS, 2000, 11 (01) : 29 - 35
  • [49] The value of quantitative EEG in differential diagnosis of Alzheimer's disease and subcortical vascular dementia
    Gawel, M.
    Zalewska, E.
    Szmidt-Salkowska, E.
    Kowalski, J.
    JOURNAL OF THE NEUROLOGICAL SCIENCES, 2009, 283 (1-2) : 265 - 265
  • [50] Differences in quantitative EEG between frontotemporal dementia and Alzheimer's disease as revealed by LORETA
    Nishida, K.
    Yoshimura, M.
    Isotani, T.
    Yoshida, T.
    Kitaura, Y.
    Saito, A.
    Mii, H.
    Kato, M.
    Takekita, Y.
    Suwa, A.
    Morita, S.
    Kinoshita, T.
    CLINICAL NEUROPHYSIOLOGY, 2011, 122 (09) : 1718 - 1725