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用于动态脑电图记录的运动影响电极 - 组织界面特征分析

Motion-Affected Electrode-Tissue Interface Characterization for Ambulatory EEG Recording.

作者信息

Yousefi Tayebeh, Dabbaghian Alireza, Kassiri Hossein

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:4479-4482. doi: 10.1109/EMBC44109.2020.9176671.

Abstract

Motion artifacts are arguably the most important issue in the development of wearable ambulatory EEG devices. Designing circuits and systems capable of high-quality EEG recording regardless of these artifacts requires a clear understanding of how the electrode-skin interface is affected by physical motions. In this work, first, we report statistically-significant experimental characterization results of electrodeskin interface impedance for dry contact and non-contact electrodes in the presence of various motions. This leads to a model describing the motion-induced electrode-skin interface impedance variations for these electrodes. Next, a critical review of the possible analog front-end circuits for surface EEG recording is presented, followed by theoretical circuit analysis discussing the effect of electrode movements on the operation of these circuits. Inspired by the developed model and the analytical review, a novel front-end architecture capable of extracting motion from the EEG signal during the amplification stage is presented and experimentally characterized.

摘要

运动伪迹可以说是可穿戴式动态脑电图设备开发中最重要的问题。设计出能够在存在这些伪迹的情况下进行高质量脑电图记录的电路和系统,需要清楚地了解电极 - 皮肤界面是如何受到身体运动影响的。在这项工作中,首先,我们报告了在存在各种运动的情况下,干接触电极和非接触电极的电极 - 皮肤界面阻抗的具有统计学意义的实验表征结果。这得出了一个描述这些电极因运动引起的电极 - 皮肤界面阻抗变化的模型。接下来,对用于表面脑电图记录的可能的模拟前端电路进行了批判性综述,随后进行了理论电路分析,讨论了电极移动对这些电路运行的影响。受所开发模型和分析性综述的启发,提出了一种能够在放大阶段从脑电图信号中提取运动信息的新型前端架构,并对其进行了实验表征。

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