Noninvasive Fetal ECG: the PhysioNet/Computing in Cardiology Challenge 2013.

Computing in cardiology Pub Date : 2013-03-01
Ikaro Silva, Joachim Behar, Reza Sameni, Tingting Zhu, Julien Oster, Gari D Clifford, George B Moody
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引用次数: 0

Abstract

The PhysioNet/CinC 2013 Challenge aimed to stimulate rapid development and improvement of software for estimating fetal heart rate (FHR), fetal interbeat intervals (FRR), and fetal QT intervals (FQT), from multichannel recordings made using electrodes placed on the mother's abdomen. For the challenge, five data collections from a variety of sources were used to compile a large standardized database, which was divided into training, open test, and hidden test subsets. Gold-standard fetal QRS and QT interval annotations were developed using a novel crowd-sourcing framework. The challenge organizers used the hidden test subset to evaluate 91 open-source software entries submitted by 53 international teams of participants in three challenge events, estimating FHR, FRR, and FQT using the hidden test subset, which was not available for study by participants. Two additional events required only user-submitted QRS annotations to evaluate FHR and FRR estimation accuracy using the open test subset available to participants. The challenge yielded a total of 91 open-source software entries. The best of these achieved average estimation errors of 187bpm2 for FHR, 20.9 ms for FRR, and 152.7 ms for FQT. The open data sets, scoring software, and open-source entries are available at PhysioNet for researchers interested on working on these problems.

无创胎儿心电图:2013 年 PhysioNet/Computing in Cardiology Challenge。
PhysioNet/CinC 2013 挑战赛旨在促进软件的快速开发和改进,以便通过放置在母亲腹部的电极进行多通道记录,估算胎儿心率 (FHR)、胎儿搏动间期 (FRR) 和胎儿 QT 间期 (FQT)。在挑战赛中,我们使用了来自不同来源的五个数据集来编制一个大型标准化数据库,该数据库分为训练、开放测试和隐藏测试子集。金标准胎儿 QRS 和 QT 间期注释是利用新颖的众包框架开发的。挑战赛组织者使用隐藏测试子集对 53 个国际参赛团队在三项挑战赛中提交的 91 个开源软件项目进行了评估,使用隐藏测试子集估算了 FHR、FRR 和 FQT(参赛者无法使用该子集进行研究)。另外两项比赛只要求用户提交 QRS 注释,以评估使用开放测试子集进行 FHR 和 FRR 估算的准确性。此次挑战赛共收到 91 个开源软件参赛作品。其中最好的软件的 FHR 平均估计误差为 187bpm2,FRR 平均估计误差为 20.9 ms,FQT 平均估计误差为 152.7 ms。有兴趣研究这些问题的研究人员可在 PhysioNet 上查阅开放数据集、评分软件和开源作品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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