脑电信号处理检测工作记忆任务中脑卒中相关轻度认知障碍

2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME) Pub Date : 2017-10-01 DOI:10.1109/ICABME.2017.8167557

N. Al-Qazzaz, S. Ali, S. A. Ahmad, J. Escudero

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引用次数: 7

摘要

本研究的目的是利用近似熵(ApEn)和排列熵(PerEn)来揭示脑电图(EEG)中的标记。采用基于小波变换的方法对15例脑卒中相关轻度认知障碍(MCI)患者和15例健康对照者在工作记忆(WM)任务中的脑电伪影进行了去除。采用t检验(p < 0.05)检验MCIs患者ApEn和PerEn的不规则性较对照组降低的假设。ApEn和PerEn显示MCI患者脑电图的不规则性降低。因此，ApEn和PerEn可以作为MCI检测和识别的相关标记物，脑电图可以作为检测MCI患者背景活动的有价值的工具。

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Stroke-related mild cognitive impairment detection during working memory tasks using EEG signal processing

The aim of the present study was to reveal markers from the electroencephalography (EEG) using approximation entropy (ApEn) and permutation entropy (PerEn). EEGs' of 15 stroke-related patients with mild cognitive impairment (MCI) and 15 control healthy subjects during a working memory (WM) task have EEG artifacts were removed using a wavelet (WT) based method. A t-test (p < 0.05) was used to test the hypothesis that the irregularity (ApEn and PerEn) in MCIs was reduced in comparison with control subjects. ApEn and PerEn showed reduced irregularity in the EEGs of MCI patients. Therefore, ApEn and PerEn could be used as markers associated with MCI detection and identification and the EEG could be a valuable tool for inspecting the background activity in the identification of patients with MCI.

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2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)

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