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Heart rate monitoring in ultra-high-field MRI using frequency information obtained from video signals of the human skin compared to electrocardiography and pulse oximetry

Heart rate monitoring in ultra-high-field MRI using frequency information obtained from video... Abstract Videos of the human skin contain subtle color variations associated with the blood volume pulse. This remote photoplethysmography signal can be used for heart rate monitoring and represents an alternative to signals obtained from contact-based hardware. We developed an algorithm that estimates the heart rate in real-time from photoplethysmography signals and evaluate its performance in the context of ultra-high-field magnetic resonance imaging. We compare its accuracy to heart rate values estimated from electrocardiography and finger pulse oximetry triggers, obtained from MR vendor-provided hardware. For eight subjects, two experiments are conducted with the patient table outside and inside a 7 Tesla scanner. During both 5 min setups, heart rates from the algorithm and contact-based methods are stored. Their comparison suggests technical feasibility of the contactless method but that it is inferior in accuracy compared to contact-based hardware and that low heart rates (≤50 beats per minute) and adequate illumination are major challenges for practical feasibility. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Current Directions in Biomedical Engineering de Gruyter

Heart rate monitoring in ultra-high-field MRI using frequency information obtained from video signals of the human skin compared to electrocardiography and pulse oximetry

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Publisher
de Gruyter
Copyright
Copyright © 2015 by the
ISSN
2364-5504
eISSN
2364-5504
DOI
10.1515/cdbme-2015-0018
Publisher site
See Article on Publisher Site

Abstract

Abstract Videos of the human skin contain subtle color variations associated with the blood volume pulse. This remote photoplethysmography signal can be used for heart rate monitoring and represents an alternative to signals obtained from contact-based hardware. We developed an algorithm that estimates the heart rate in real-time from photoplethysmography signals and evaluate its performance in the context of ultra-high-field magnetic resonance imaging. We compare its accuracy to heart rate values estimated from electrocardiography and finger pulse oximetry triggers, obtained from MR vendor-provided hardware. For eight subjects, two experiments are conducted with the patient table outside and inside a 7 Tesla scanner. During both 5 min setups, heart rates from the algorithm and contact-based methods are stored. Their comparison suggests technical feasibility of the contactless method but that it is inferior in accuracy compared to contact-based hardware and that low heart rates (≤50 beats per minute) and adequate illumination are major challenges for practical feasibility.

Journal

Current Directions in Biomedical Engineering – de Gruyter

Published: Sep 1, 2015

References

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  • Improvements in remote detection of photoplethysmographic systolic and diastolic peaks using a digital camera
  • Exploiting spatial redundancy of image sensor for motion robust rPPG
  • Remote plethysmo-graphic imaging using ambient light
  • Initial results of cardiac imaging at 7T
  • Initial results of cardiac imaging at 7T
  • OpenCV is an open-source, computer-vision library for extracting and processing meaningful data from images
  • Improvements in remote cardiopulmonary measurement using a five band digital camera
  • Advancements in noncontact, multiparameter physiological measurements using a webcam
  • Photoplethysmography and its application in clinical physiological measurement
  • ROOT - an object oriented data analysis framework
  • Simultaneous monitoring of cardiac and respiratory signals using a markerless optical system