An Approach to Compute Fetal Cardiac Biomarkers from the Abdominal Electrocardiogram

IF 5.6 4区 医学 Q1 ENGINEERING, BIOMEDICAL
Irbm Pub Date : 2025-03-14 DOI:10.1016/j.irbm.2025.100886
Paula Romina Soria , Pablo Daniel Cruces , César Federico Caiafa , Pedro David Arini
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引用次数: 0

Abstract

Objective: The fetal electrocardiogram (FECG) can be recorded from the 20th week of gestation. The aim of this work is to determine fetal cardiac biomarkers from non-invasive cardiac signals that may be useful in the assessment of fetal health. Methods: We have developed an algorithm to obtain FECG fiducial points. It started by discriminating fetal heartbeats based on the relative location between fetal and maternal QRS complexes. An average beat is derived from the abdominal electrocardiogram (AECG) using 20 beats with a correlation greater than 0.95 and stable RR-interval, based on data from 12 fetuses (38th - 42nd weeks). We have implemented a combination between quaternion algebra and principal component analysis (Q-PCA method) to determine the onset and end of FECG waves by analyzing the angular velocity of the heart electrical vector. To validate our findings, we compared them with measurements obtained from the direct fetal electrocardiogram (DFECG), as a benchmark. Results: The values calculated by the Q-PCA method, as well as their correlation and the p-value in relation to the DFECG, were as follows: PR interval: 125.1±19.8 ms (ρ=0.97, p<2.39e7), QRS complex: 73.0±4.4 ms (ρ=0.67, p<1.74e2), QT interval: 261.1±28.5 ms (ρ=0.84, p<7.05e4) and QTc interval: 388.3±35.9 ms (ρ=0.79, p<2.27e3). Conclusion: Given its importance and the measurement performance achieved, the methodology presented represents a significant potential tool for improving the diagnosis of fetal health.

Abstract Image

从腹部心电图计算胎儿心脏生物标志物的方法
目的:从妊娠第20周开始记录胎儿心电图。这项工作的目的是从非侵入性心脏信号中确定胎儿心脏生物标志物,这可能对评估胎儿健康有用。方法:我们开发了一种获取FECG基准点的算法。它首先根据胎儿和母体QRS复合物之间的相对位置来区分胎儿的心跳。根据12个胎儿(38 - 42周)的数据,通过20次腹部心电图(AECG)得出平均心跳,相关性大于0.95,rr -间隔稳定。我们实现了四元数代数和主成分分析(Q-PCA)的结合,通过分析心脏电矢量的角速度来确定feg波的开始和结束。为了验证我们的发现,我们将其与直接胎儿心电图(DFECG)作为基准进行了比较。结果:用Q-PCA方法计算的值及其与DFECG的相关性和p值分别为:PR区间:125.1±19.8 ms (ρ=0.97, p<2.39e−7),QRS复合体:73.0±4.4 ms (ρ=0.67, p<1.74e−2),QT间期:261.1±28.5 ms (ρ=0.84, p<7.05e−4),QTc区间:388.3±35.9 ms (ρ=0.79, p<2.27e−3)。结论:鉴于其重要性和测量性能的实现,所提出的方法是一个重要的潜在工具,以提高胎儿健康的诊断。
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来源期刊
Irbm
Irbm ENGINEERING, BIOMEDICAL-
CiteScore
10.30
自引率
4.20%
发文量
81
审稿时长
57 days
期刊介绍: IRBM is the journal of the AGBM (Alliance for engineering in Biology an Medicine / Alliance pour le génie biologique et médical) and the SFGBM (BioMedical Engineering French Society / Société française de génie biologique médical) and the AFIB (French Association of Biomedical Engineers / Association française des ingénieurs biomédicaux). As a vehicle of information and knowledge in the field of biomedical technologies, IRBM is devoted to fundamental as well as clinical research. Biomedical engineering and use of new technologies are the cornerstones of IRBM, providing authors and users with the latest information. Its six issues per year propose reviews (state-of-the-art and current knowledge), original articles directed at fundamental research and articles focusing on biomedical engineering. All articles are submitted to peer reviewers acting as guarantors for IRBM''s scientific and medical content. The field covered by IRBM includes all the discipline of Biomedical engineering. Thereby, the type of papers published include those that cover the technological and methodological development in: -Physiological and Biological Signal processing (EEG, MEG, ECG…)- Medical Image processing- Biomechanics- Biomaterials- Medical Physics- Biophysics- Physiological and Biological Sensors- Information technologies in healthcare- Disability research- Computational physiology- …
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