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Early Detection of Mild Cognitive Impairment, Dementia and Alzheimer’s Using Qeeg

Author

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  • Norsiah Fauzan
  • Amran Nur Hurunain

Abstract

This article reports the biomarkers of the Mild Cognitive Impairment (MCI) among the elderly group aged around 60 -75 years old by analyzing the EEG signals recorded by using the quantitative electroencephalograph (qEEG). There is growing evidence that EEG analysis in resting state condition are useful in early detection of neural signatures of Alzheimer’s and dementia. EEG findings and analysis shows potential of discriminating MCI, Alzheimer’s and dementia. In this research, the purpose is to 1) develop the indexes for each of the EEG bands and sub-bands such as delta (1.5 – 3.5 Hz), theta (3.3 – 7.5 Hz), alpha ( 8 – 12 Hz), beta 1 (15 – 18 Hz) and beta 2 (22 – 30 Hz); 2) provide reference for early diagnosis; 3) extract and analyze the brainwave pattern of MCI and cognitively healthy group. This study involved 19 channel resting state EEG from a total of 30 subjects, 18 diagnosed as having MCI and 12 cognitively healthy elderly with criteria for inclusion if the mini mental state examination (MMSE) score is more than or equal to 28, based on the age and educational level. Development of qEEG index started by decomposition of EEG by performing Fourier analysis, averaging and normalizing the value from the 19 channels to obtain the z-score. Findings showed promise of utility in early detection of Alzheimer’s. Notably, 1) Increases in delta/ theta posterior temporal and prefrontal area i.e., H(6.64) vs. MCI(26.29); beta temporal region, 2) Decreases in alpha at sensory motor region i.e., H(0.27) vs. MCI(0.23).

Suggested Citation

  • Norsiah Fauzan & Amran Nur Hurunain, 2022. "Early Detection of Mild Cognitive Impairment, Dementia and Alzheimer’s Using Qeeg," European Journal of Natural Sciences and Medicine, European Center for Science Education and Research, vol. 5, January -.
  • Handle: RePEc:eur:ejnmjr:44
    DOI: 10.26417/ejis.v1i3.p149-153
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