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优化通用变换系数重建 12 导联心电图信号的贴片式监测传感器的导联位置。

Optimal Lead Position in Patch-Type Monitoring Sensors for Reconstructing 12-Lead ECG Signals with Universal Transformation Coefficient.

机构信息

Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 03080, Korea.

Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul 03080, Korea.

出版信息

Sensors (Basel). 2020 Feb 11;20(4):963. doi: 10.3390/s20040963.

DOI:10.3390/s20040963
PMID:32053945
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7071434/
Abstract

The aim of this study was to reconstruct a 12-lead electrocardiograph (ECG) with a universal transformation coefficient and find the appropriate electrode position and shape for designing a patch-type ECG sensor. A 35-channel ECG monitoring system was developed, and 14 subjects were recruited for the experiment. A feedforward neural network with one hidden layer was applied to train the transformation coefficient. Three electrode shapes (5 cm × 5 cm square, 10 cm × 10 cm square, and right-angled triangle) were considered for the patch-type ECG sensor. The mean correlation coefficient (CC) and minimum CC methods were applied to evaluate the reconstruction performance. The average CCs between the standard 12-lead ECG and reconstructed 12-lead ECG were 0.860, 0.893, and 0.893 for a 5 cm × 5 cm square, 10 cm × 10 cm square, and right-angled triangle shape. The right-angled triangle showed the highest performance among the considered shapes. The results also suggested that the bottom of the central area of the chest was the most suitable position for attaching the patch-type ECG sensor.

摘要

本研究旨在利用通用变换系数重构十二导联心电图,并找到设计贴片式心电图传感器的合适电极位置和形状。开发了一个 35 通道心电图监测系统,并招募了 14 名受试者进行实验。应用具有一个隐藏层的前馈神经网络来训练变换系数。考虑了三种电极形状(5cm×5cm 方形、10cm×10cm 方形和直角三角形)用于贴片式心电图传感器。采用平均相关系数(CC)和最小 CC 方法评估重构性能。5cm×5cm 方形、10cm×10cm 方形和直角三角形的标准 12 导联心电图和重构的 12 导联心电图之间的平均 CC 分别为 0.860、0.893 和 0.893。在所考虑的形状中,直角三角形表现出最高的性能。结果还表明,胸部中央区域的底部是粘贴贴片式心电图传感器的最佳位置。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/6e38c07519cd/sensors-20-00963-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/210ef83efb9e/sensors-20-00963-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/d2bea22da9ae/sensors-20-00963-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/6e38c07519cd/sensors-20-00963-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/7ec99f398824/sensors-20-00963-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/6033a9e81571/sensors-20-00963-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/dfe8669c620b/sensors-20-00963-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/210ef83efb9e/sensors-20-00963-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/d2bea22da9ae/sensors-20-00963-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e4a/7071434/6e38c07519cd/sensors-20-00963-g007.jpg

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Reconstruction of the 12-lead ECG using a novel MR-compatible ECG sensor network.使用新型兼容磁共振的心电图传感器网络重建 12 导联心电图。
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Reconstruction of 12-lead ECG Using a Single-patch Device.使用单贴片设备重建12导联心电图
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