基于零空间盲源分离的胎儿异位心电信号提取

L. Taha, E. Abdel-Raheem
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引用次数: 0

摘要

本文的目的是应用盲源分离(BSS)技术提取异位搏胎儿心电图信号。我们使用了一种新的确定性BSS算法——零空间变换矩阵(NSITM)。心电信号被用来计算ITM。然后,从ITM的零空间中提取feg信号和母体ECG (MECG)信号。结果表明,当胎儿与母亲的信噪比(fmSNR)从−30 dB增加到0 dB时,与本研究中使用的其他算法相比,Physionet合成的ECG数据的提取性能(质量信噪比qSNR和相关性$r$)有了显著改善。使用NSITM算法,当fmSNR = 0 dB时,qSNR和$r$的最大值分别为5.95 dB和0.871。当fmSNR =−30 dB时,qSNR和$r$的最小值分别为2.27 dB和0.726。研究表明,BSS型NSITM是一种可行的提取异位心跳受试者脑电图信号的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extraction of Fetal ECG Signal with Ectopic Beats using Blind Source Separation Based Null Space Approach
The aim of this paper is to apply blind source separation (BSS) to extract fetal electrocardiogram (FECG) signal with ectopic beat. We use a novel deterministic BSS algorithm type null space transformation matrix (NSITM). The ECG signals are used to compute the ITM. Then, the FECG signal and maternal ECG (MECG) signals are extracted from the null space of the ITM. Results from Physionet synthesized ECG data show considerable improvement in extraction performance (quality signal-to-noise ratio qSNR and correlation $r$) over other algorithms used in this work, when the fetal-to-maternal signal-to-noise ratio (fmSNR) increases from −30 dB to 0 dB. Using the NSITM algorithm, the maximum values of qSNR and $r$ are 5.95 dB and 0.871, respectively, when fmSNR is equal to 0 dB. The minimum values of qSNR and $r$ are 2.27 dB and 0.726, respectively, when fmSNR is equal to −30 dB. The study demonstrates that the BSS type NSITM is a feasible algorithm for extracting FECG signals for subjects with ectopic beats.
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