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首页> 外文期刊>Medical engineering & physics. >Adaptive independent component analysis of multichannel electrogastrograms.
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Adaptive independent component analysis of multichannel electrogastrograms.

机译:多通道胃电图的自适应独立成分分析。

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摘要

The electrogastrogram (EGG), a cutaneous measurement of gastric electrical activity, can be severely contaminated by endogenous biological noise sources such as respiratory signal. Therefore it is important to establish effective artifact removal methods. In this paper, a novel blind signal separation method with a flexible non-linearity is introduced and applied to extract the gastric slow wave from multichannel EGGs. Simulation results show that our algorithm is able to separate a wide range of source signals, including mixtures of Gaussian sources. On real data, we demonstrate the successful applications of our procedure to extract the gastric slow wave from multichannel EGGs. As a result, the extracted clean gastric slow wave can be used to facilitate further analysis, e.g. as a reference signal for multichannel adaptive enhancement of the EGG.
机译:胃电活动的皮肤测量电图(EGG)可能会被诸如呼吸信号之类的内源性生物噪声源严重污染。因此,建立有效的工件去除方法很重要。本文介绍了一种具有灵活非线性的新型盲信号分离方法,并将其应用于从多通道EGG中提取胃慢波。仿真结果表明,我们的算法能够分离各种信号源,包括高斯信号源的混合信号。在真实数据上,我们证明了该程序从多通道EGG提取胃慢波的成功应用。结果,所提取的干净的胃慢波可用于促进进一步的分析,例如。作为EGG的多通道自适应增强的参考信号。

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