摘要
心阻抗血流图(ICG)在心血管疾病患者心功能评价中发挥重要作用。针对ICG信号的测量容易受运动伪迹的干扰问题,本文提出了两步频域集合经验模态分解(EEMD)和典型相关性分析(CCA)的去噪方法。首先,将ICG信号、心电图(ECG)分别与运动信号做第一步频域EEMD-CCA,将相关性系数高的成分置零来抑制主要运动伪迹。其次,将得到的ECG和ICG信号做第二步频域EEMD-CCA,获取这两组生理信号之间的共同成分来进一步去噪。最后,利用这些共同成分来重构ICG信号。本研究招募了30名志愿者参与测试,结果表明,使用本文提出的去噪方法后,ICG信号的质量有大幅度的提升,可为后续的心血管疾病诊断和分析提供支撑。
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.
作者
解尧
杨东
余洪龙
解启莲
XIE Yao;YANG Dong;YU Honglong;XIE Qilian(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;School of Clinical Medical,Anhui Medical University,Hefei 230032,P.R.China)
出处
《生物医学工程学杂志》
EI
CAS
北大核心
2024年第5期986-994,共9页
Journal of Biomedical Engineering
基金
国家重点研发计划(2020YFC2004400)。
关键词
典型相关性分析
心阻抗血流图
运动伪迹
去噪方法
Canonical correlation analysis
Impedance cardiography
Motion artifacts
Denoising method
