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Motion artifacts in capacitive ECG monitoring systems: a review of existing models and reduction techniques
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Abstract
Current research focuses on improving electrocardiogram (ECG) monitoring systems to enable real-time and long-term usage, with a specific focus on facilitating remote monitoring of ECG data. This advancement is crucial for improving cardiovascular health by facilitating early detection and management of cardiovascular disease (CVD). To efficiently meet these demands, user-friendly and comfortable ECG sensors that surpass wet electrodes are essential. This has led to increased interest in ECG capacitive electrodes, which facilitate signal detection without requiring gel preparation or direct conductive contact with the body. This feature makes them suitable for wearables or integrated measurement devices. However, ongoing research is essential as the signals they measure often lack sufficient clinical accuracy due to susceptibility to interferences, particularly Motion Artifacts (MAs). While our primary focus is on studying MAs, we also address other limitations crucial for designing a high Signal-to-Noise Ratio (SNR) circuit and effectively mitigating MAs. The literature on the origins and models of MAs in capacitive electrodes is insufficient, which we aim to address alongside discussing mitigation methods. We bring attention to digital signal processing approaches, especially those using reference signals like Electrode-Tissue Impedance (ETI), as highly promising. Finally, we discuss its challenges, proposed solutions, and offer insights into future research directions.
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obtained her B.S. degree in Electronic Engineering from Shariaty University, Tehran, Iran, in 2011, followed by her M.S. degree in Electronic Engineering from Iran University of Science and Technology, Tehran, Iran, with a focus on Analog Integrated Circuits in 2014. Subsequently, she amassed seven years of experience as an R&D engineer in industry, specializing in real-time embedded systems, digital hardware design, and digital signal processing.
Currently, she is pursuing her Ph.D. at the Institute of Biomedical Technologies at Auckland University of Technology. Her research focuses on the electronic design of biopotential electrodes and biomedical signal processing.
a Professor at the Department of Electrical and Electronic Engineering, Auckland University of Technology, received his PhD in Biomedical Engineering from Flinders University of Australia in 2002, focusing on computer-aided diagnosis of cardiac arrhythmia. Prior to this, he completed his MSc in Electrical Engineering at the University of Tehran. With research interests primarily in Smart Patient Monitoring, Artificial Intelligence, Biomedical signal and image processing, as well as Embedded and reconfigurable systems, he holds honorary and visiting Professorships at Mälardalen University, Sweden, and Guangdong University of Technology, China. GholamHosseini has contributed to over 190 book chapters, journal papers, and conference publications. As a Senior Member of IEEE and Chapter Chair of Engineering in Medicine and Biology Society (EMBS) of IEEE New Zealand North Section, he remains actively engaged in professional networks. Notably, he has served as the principal investigator on numerous funded projects, including a recent Precision Driven Health (PDH)-funded initiative on Vital Signs Monitoring.
is currently a Professor of Mechanical Engineering and the Director of the Institute of Biomedical Technologies at Auckland University of Technology. His research focuses on measuring and modeling the cardiovascular system to enhance cardiovascular risk management in primary and community care, as well as advancing the measurement of electrical signals produced by the human body.
Before joining AUT, he spent 15 years serving as Chief Technology Officer and Managing Director at a medical device company. There, he spearheaded the development of an innovative non-invasive cardiovascular product, overseeing its journey from conception to manufacturing, obtaining certifications from the US FDA and European authorities, protecting its intellectual property, negotiating worldwide licensing and distribution agreements, and eventually facilitating its trade sale. Prior to this role, he led software development for industrial, multi-axis cutting robots.
Dr. Lowe earned his PhD from the University of Auckland, focusing on fuzzy logic applications in patient monitoring during anesthesia. He also holds a Bachelor of Engineering degree from the same university, specializing in dynamics and control within the mechanical engineering department.
currently serves as a Senior Lecturer at Auckland University of Technology, where his primary research interests lie in the design, development, testing, verification, and analysis of Cyber-Physical Systems (CPS) within Industrial Automation, Industry 4.0, Smart Factories, Smart Homes, Internet-of-Things (IoT), and Healthcare domains.
Dr. Kuo obtained his PhD in Computer Systems Engineering from the University of Auckland in 2015. He is actively engaged in leading the Next Generation Systems theme within the Software Engineering Research Centre (SERC). This thematic area is dedicated to advancing research in the design, development, verification, analysis, and establishment of standards to address the evolving needs, scale, and complexity of Next Generation Systems.
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3165Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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