In Autumn 2020, DOAJ will be relaunching with a new website with updated functionality, improved search, and a simplified application form. More information is available on our blog. Our API is also changing.

Hide this message

Real-time QRS detection using integrated variance for ECG gated cardiac MRI

Current Directions in Biomedical Engineering. 2016;2(1):255-258 DOI 10.1515/cdbme-2016-0057


Journal Homepage

Journal Title: Current Directions in Biomedical Engineering

ISSN: 2364-5504 (Online)

Publisher: De Gruyter

LCC Subject Category: Medicine

Country of publisher: Germany

Language of fulltext: English

Full-text formats available: PDF, XML



Schmidt Marcus (Department of Medical Engineering, Otto-von-Guericke-University of Magdeburg, Germany)

Krug Johannes W. (Department of Medical Engineering, Otto-von-Guericke-University of Magdeburg, Germany)

Rose Georg (Department of Medical Engineering, Otto-von-Guericke-University of Magdeburg, Germany)


Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 14 weeks


Abstract | Full Text

During magnetic resonance imaging (MRI), a patient’s vital signs are required for different purposes. In cardiac MRI (CMR), an electrocardiogram (ECG) of the patient is required for triggering the image acquisition process. However, a reliable QRS detection of an ECG signal acquired inside an MRI scanner is a challenging task due to the magnetohydrodynamic (MHD) effect which interferes with the ECG. The aim of this work was to develop a reliable QRS detector usable inside the MRI which also fulfills the standards for medical devices (IEC 60601-2-27). Therefore, a novel real-time QRS detector based on integrated variance measurements is presented. The algorithm was trained on ANSI/AAMI EC13 test waveforms and was then applied to two databases with 12-lead ECG signals recorded inside and outside an MRI scanner. Reliable results for both databases were achieved for the ECG signals recorded inside (DBMRI: sensitivity Se = 99.94%, positive predictive value +P = 99.84%) and outside (DBInCarT: Se = 99.29%, +P = 99.72%) the MRI. Due to the accurate R-peak detection in real-time this can be used for monitoring and triggering in MRI exams.