The CirCor DigiScope Phonocardiogram Dataset

A total number of 5272 heart sound recordings were collected from the main four auscultation locations of 1568 subjects, aged between 0 and 21 years (mean ± STD = 6.1 ± 4.3 years), with a duration between 4.8 to 80.4 seconds (mean ± STD = 22.9 ± 7.4 s), totaling more than 33.5 hours of recording. Each cardiac murmur in the dataset has been annotated in detail by a human annotator, in terms of timing, shape, pitch, grading, quality and location. Moreover, segmentation annotations regarding the location of fundamental heart sounds (S1 and S2) in the recordings have been obtained using a semi-supervised scheme. The segmentation annotations were performed by voting between three state-of-the-art machine-based algorithms. An expert annotator later studied the consensus and mismatches between the algorithms beat-by-beat and performed a manual annotation whenever the algorithms had disagreed or were not acceptable for the expert. To date, the dataset is the largest publicly available pediatric heart sound dataset, supporting deeper research on the topic of auscultation-based health recommendation systems. The dataset is being used in the George B. Moody PhysioNet Challenge 2022 on Heart Murmur Detection from Phonocardiogram Recordings.

总计收集了5272例心音记录，来自1568名年龄在0至21岁之间（平均±标准差=6.1±4.3岁）的受试者的主要四个听诊位置，记录时长介于4.8至80.4秒（平均±标准差=22.9±7.4秒），累计超过33.5小时。数据集中的每一例心脏杂音均由人工标注员进行了详细的标注，包括时间、形状、音调、等级、质量和位置。此外，通过半监督方案获得了关于记录中基本心音（S1和S2）位置的分割标注。分割标注是通过三个最先进的基于机器的算法之间的投票来完成的。随后，一名专家标注员对算法之间的共识和差异进行了逐拍分析，并在算法意见不一致或不符合专家要求时进行了手动标注。截至目前，该数据集是公开可用的最大儿童心音数据集，支持对基于听诊的健康推荐系统主题的深入研究。该数据集被用于2022年乔治·B·穆迪生理网络挑战赛，该挑战赛旨在从心音图记录中检测心脏杂音。