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本文引用的文献

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An open-source automated algorithm for removal of noisy beats for accurate impedance cardiogram analysis.用于准确阻抗心图分析的去噪心跳自动开源算法。
Physiol Meas. 2020 Aug 11;41(7):075002. doi: 10.1088/1361-6579/ab9b71.
2
[Processing of impedance cardiogram differential for non-invasive cardiac function detection].[用于无创心功能检测的阻抗心动图微分处理]
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2019 Feb 25;36(1):50-58. doi: 10.7507/1001-5515.201804014.
3
Cardiac output measurement during exercise in COPD: A comparison of dye dilution and impedance cardiography.慢性阻塞性肺疾病患者运动时的心输出量测量:染料稀释法与阻抗心动图法的比较
Clin Respir J. 2019 Apr;13(4):222-231. doi: 10.1111/crj.13002. Epub 2019 Feb 28.
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SPECMAR: fast heart rate estimation from PPG signal using a modified spectral subtraction scheme with composite motion artifacts reference generation.SPECMAR:使用改进的带复合运动伪影参考生成的频谱相减方案从 PPG 信号中快速估计心率。
Med Biol Eng Comput. 2019 Mar;57(3):689-702. doi: 10.1007/s11517-018-1909-x. Epub 2018 Oct 22.
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Toward a better noninvasive assessment of preejection period: A novel automatic algorithm for B-point detection and correction on thoracic impedance cardiogram.旨在更好地无创评估射血前期:一种新的基于胸阻抗心动图的 B 点检测和校正自动算法。
Psychophysiology. 2018 Aug;55(8):e13072. doi: 10.1111/psyp.13072. Epub 2018 Mar 7.
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Time-frequency Features for Impedance Cardiography Signals During Anesthesia Using Different Distribution Kernels.使用不同分布核的麻醉期间阻抗心动图信号的时频特征
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Efficient reference-free adaptive artifact cancellers for impedance cardiography based remote health care monitoring systems.用于基于阻抗心动图的远程医疗监测系统的高效无参考自适应伪影消除器。
Springerplus. 2016 Jun 17;5(1):770. doi: 10.1186/s40064-016-2461-5. eCollection 2016.
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TROIKA: a general framework for heart rate monitoring using wrist-type photoplethysmographic signals during intensive physical exercise.TRIOCA:一种在高强度体育锻炼期间使用腕部光电容积脉搏波信号进行心率监测的通用框架。
IEEE Trans Biomed Eng. 2015 Feb;62(2):522-31. doi: 10.1109/TBME.2014.2359372. Epub 2014 Sep 19.
9
[Research on ECG de-noising method based on ensemble empirical mode decomposition and wavelet transform using improved threshold function].基于集成经验模态分解和使用改进阈值函数的小波变换的心电图去噪方法研究
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2014 Jun;31(3):567-71.
10
CANONICAL CORRELATION ANALYSIS BETWEEN TIME SERIES AND STATIC OUTCOMES, WITH APPLICATION TO THE SPECTRAL ANALYSIS OF HEART RATE VARIABILITY.时间序列与静态结果之间的典型相关分析及其在心率变异性频谱分析中的应用
Ann Appl Stat. 2013 Mar 1;7(1):570-587. doi: 10.1214/12-aoas601.

基于两步谱总体经验模态分解和典型相关分析的运动阻抗心动图去噪方法研究

[Research on motion impedance cardiography de-noising method based on two-step spectral ensemble empirical mode decomposition and canonical correlation analysis].

作者信息

Xie Yao, Yang Dong, Yu Honglong, Xie Qilian

机构信息

School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, P. R. China.

Anhui Tongling Bionic Technology Co. Ltd, Hefei 230601, P. R. China.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024 Oct 25;41(5):986-994. doi: 10.7507/1001-5515.202210059.

DOI:10.7507/1001-5515.202210059
PMID:39462667
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11527760/
Abstract

Impedance cardiography (ICG) is essential in evaluating cardiac function in patients with cardiovascular diseases. Aiming at the problem that the measurement of ICG signal is easily disturbed by motion artifacts, this paper introduces a de-noising method based on two-step spectral ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA). Firstly, the first spectral EEMD-CCA was performed between ICG and motion signals, and electrocardiogram (ECG) and motion signals, respectively. The component with the strongest correlation coefficient was set to zero to suppress the main motion artifacts. Secondly, the obtained ECG and ICG signals were subjected to a second spectral EEMD-CCA for further denoising. Lastly, the ICG signal is reconstructed using these share components. The experiment was tested on 30 subjects, and the results showed that the quality of the ICG signal is greatly improved after using the proposed denoising method, which could support the subsequent diagnosis and analysis of cardiovascular diseases.

摘要

阻抗心动图(ICG)在评估心血管疾病患者的心功能方面至关重要。针对ICG信号测量容易受到运动伪影干扰的问题,本文介绍了一种基于两步谱总体经验模态分解(EEMD)和典型相关分析(CCA)的去噪方法。首先,分别在ICG与运动信号、心电图(ECG)与运动信号之间进行第一次谱EEMD-CCA。将相关系数最强的分量设为零,以抑制主要运动伪影。其次,对得到的ECG和ICG信号进行第二次谱EEMD-CCA以进一步去噪。最后,利用这些共享分量重建ICG信号。该实验在30名受试者身上进行测试,结果表明,使用所提出的去噪方法后,ICG信号质量得到了极大改善,可为后续心血管疾病的诊断和分析提供支持。