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Estimating Heart Rate In Echocardiography Patients Where Ecg Monitoring Was Not Performed by Andrew Parker; Arian Beqiri; Angela Mumith; Mihaela Porumb; Shan Gao; Ross Upton; Paul Leeson; Jamie O’Driscoll; Riswan Sarwar; Gary Woodward is a Medicine article available to read on EtoBox.

What is Estimating Heart Rate In Echocardiography Patients Where Ecg Monitoring Was Not Performed about?

Background: According to latest EACVI recommendations, if there is a suspected case of COVID-19, patient ECGs may not be monitored during an echocardiogram to reduce exposure and contamination. However, many cardiac parameters rely on accurate end-diastolic (ED) and end-systolic (ES) frame selection (e.g. EF and GLS), and automated methods for ED and ES extraction depend on the heart rate (HR) being present for the recorded study. Here we present a novel HR extraction method to accurately infer the heart rate from echocardiograms of the left ventricle (LV). Methods: The HR extraction approach we take requires the reduction of image dimensionality, followed by signal period extraction. Here we attempt two dimensionality reduction methods: non-negative matrix factorisation (NNMF), and a segmentation deep-learning based method. The period was then extracted from these series using autocorrelation analysis. In total, 784 DICOM image clips from stress echo acquisitions from multiple UK sites are used for testing, where the HR encoded into the meta data is compared to the output of the method. Image clips encompass a variety of heart rates (394 are at rest, 390 are at peak), a variety of

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Author

Andrew Parker; Arian Beqiri; Angela Mumith; Mihaela Porumb; Shan Gao; Ross Upton; Paul Leeson; Jamie O’Driscoll; Riswan Sarwar; Gary Woodward

Publisher

Elsevier BV

Published

2021

Language

EN

Field

Medicine (Health Sciences)