Feasibility of Capacitive ECG R-Peak Detection for Cardiac Gating in 3-T MRI

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Authors: Yijing Zhang, Ketan J. Pol, Cumhur Erdin, Alessandra Galli, Sotir F. Ouzounov, Cecilia Possanzini, Irena Zivkovic, Massimo Mischi, Eugenio Cantatore, Pieter J. A. Harpe
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Abstract

Non-contact capacitive electrodes provide a higher comfort level and can avoid unpleasant skin preparation compared to conventional wet electrodes. This work studies the feasibility of using capacitive electrodes to measure the ECG (Electrocardiogram) R-peaks for cardiac gating inside an MRI (Magnetic Resonance Imaging) environment. A phantom test setup with ECG generation, 16 capacitive electrodes, ECG acquisition hardware, and an R-peak detection algorithm, is developed. Experiments are first conducted in a 3-Tesla static field (B0) and then combined with a switching gradient field. Various gradient conditions (e.g., directions, strengths, frequencies) and respiration-mimicking motions are included. The noise levels and artifacts of the raw data are first observed. An exemplary algorithm is then adopted to extract R-peaks from multi-channel data. The results show that under a 3T static field, the R-peaks are visible both in raw data only without motion and after processing even with motion. Under gradient field, some channels or epochs are strongly affected by artifacts, while other channels or epochs still contain relatively clean ECG data. Thanks to the multi-channel approach, this can still lead to successful R-peak detection without motion. The addition of motion deteriorates the signal quality and can lead to detection failure with the adopted signal processing method. The experimental results obtained in this work reveal the feasibility of capacitive ECG R-peak detection inside 3T MRI for the first time and provide a first step toward its future application for synchronizing the MRI of the heart.

Fields of Study & Subjects

ECG Monitoring and Analysis Non-Invasive Vital Sign Monitoring Electrical and Bioimpedance Tomography

Publication details

Journal / source
IEEE Sensors Journal
Volume
26
Issue
6
Pages
8945–8955
Publication date
28 January 2026
Language
EN