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Noise reduction in capacitive ECG measurements by dedicated modelling and Kalman filtering
2024-06
会议录名称2024 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS
ISSN2837-5874
发表状态已发表
DOI10.1109/MeMeA60663.2024.10596907
摘要

Electrocardiography (ECG) measurements have been extensively used for monitoring and diagnosing cardiovascular diseases (CVDs). Traditional ECG measured with wet electrodes may be unsuitable for long-term monitoring due to the use of gels that may cause skin problems. A capacitive electrode can measure an ECG though an isolating layer and is therefore a good alternative to wet electrode for long-term ambulatory monitoring. However, current application of capacitive ECG (cECG) focuses mainly on heart-rate analysis due to its high sensitivity to noise. In the present study, by using a dynamic ECG model, we propose an extended Kalman filter (EKF) for cECG noise removal. For evaluation, cECG signals were recorded from 8 healthy subjects and processed by the proposed method. The denoised cECG were then compared with the traditional ECG recorded simultaneously using gel electrodes using the Pearson's correlation coefficient (CC) as performance metric. To assess the quality of the detailed ECG waveform, such as P and T waves, CCs were also calculated after removing the QRS complex from both signals. Our results show EKF to produce promising results in both CCs, outperforming the state-of-the-art methods. Particularly, the observed high CC in the detailed ECG waves, i.e., 0.81 on average, indicates the feasibility of morphological analysis using cECG, enabling possible clinical application of cECG.

关键词Biomedical signal processing Correlation methods Electrodes Extended Kalman filters Noise abatement Ambulatory monitoring Capacitive electrocardiography Capacitive electrodes Cardiovascular disease Dedicated modelling Dynamic electrocardiography model Isolating layer Kalman-filtering Long term monitoring Model filtering
会议名称2024 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2024
会议地点Eindhoven, Netherlands
会议日期26-28 June 2024
URL查看原文
收录类别EI
语种英语
EI入藏号20243316885131
EI主题词Electrocardiography
EI分类号461.6 Medicine and Pharmacology ; 701.1 Electricity: Basic Concepts and Phenomena ; 716.1 Information Theory and Signal Processing ; 751.4 Acoustic Noise ; 922.2 Mathematical Statistics
原始文献类型Conference article (CA)
来源库IEEE
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/362296
专题信息科学与技术学院_硕士生
信息科学与技术学院_博士生
信息科学与技术学院_PI研究组_徐林组
共同第一作者Wu Yichao
通讯作者Xu L(徐林)
作者单位
1.School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
2.Eindhoven University of Technology, Eindhoven, the Netherlands
第一作者单位信息科学与技术学院
通讯作者单位信息科学与技术学院
第一作者的第一单位信息科学与技术学院
推荐引用方式
GB/T 7714
Lin Runwei,Wu Yichao,Cheng Anyi,et al. Noise reduction in capacitive ECG measurements by dedicated modelling and Kalman filtering[C],2024.
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