Independent component analysis applied to the removal of motion artifacts from electrocardiographic signals
Independent component analysis applied to the removal of motion artifacts from electrocardiographic signals
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DOI：
10.1007/s11517-007-0293-8
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发表时间：
2008-03-01
影响因子：
3.2
通讯作者：
Landini, L.
中科院分区：
文献类型：
--
作者：
Milanesi, M.;Martini, N.;Landini, L.
心电信号会受到几种伪像的影响，这些伪像可能会隐藏感兴趣的生命体征。在这项研究中，我们应用独立分量分析(ICA)来分离运动伪影。将标准或瞬时ICA与其他两种ICA技术进行了比较，其中标准或瞬时ICA是目前在伪影去除上下文中寻址最多的ICA模型。第一种技术是一种卷积混合分离的频域方法。第二种是基于时间约束的独立分量分析，它使估计只有一个接近特定参考信号的分量。性能指标评价心电复合增强及相关心率误差。结果表明，卷积ICA和约束ICA的性能都优于标准ICA，从而为这两种方法开辟了一个新的应用领域。此外，统计分析表明，约束ICA和卷积ICA在心率估计方面没有显著差异，尽管后者在心电信号形态恢复方面克服了前者。
Electrocardiographic (ECG) signals are affected by several kinds of artifacts that may hide vital signs of interest. In this study we apply independent component analysis (ICA) to isolate motion artifacts. Standard or instantaneous ICA, which is currently the most addressed ICA model within the context of artifact removal, is compared to two other ICA techniques. The first technique is a frequency domain approach to convolutive mixture separation. The second is based on temporally constrained ICA, which enables the estimation of only one component close to a particular reference signal. Performance indexes evaluate ECG complex enhancement and relevant heart rate errors. Our results show that both convolutive and constrained ICA implementations perform better than standard ICA, thus opening up a new field of application for these two methods. Moreover, statistical analysis reveals that constrained ICA and convolutive ICA do not significantly differ concerning heart rate estimation, even though the latter overcomes the former in ECG morphology recovery.