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

Autor: Xie Y; 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., Yang D; 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., Yu H; Anhui Tongling Bionic Technology Co. Ltd, Hefei 230601, P. R. China., Xie Q; Anhui Tongling Bionic Technology Co. Ltd, Hefei 230601, P. R. China.; School of Clinical Medical, Anhui Medical University, Hefei 230032, P. R. China.
Jazyk: čínština
Zdroj: Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi [Sheng Wu Yi Xue Gong Cheng Xue Za Zhi] 2024 Oct 25; Vol. 41 (5), pp. 986-994.
DOI: 10.7507/1001-5515.202210059
Abstrakt: 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.
Databáze: MEDLINE
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