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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Transactions on...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Transactions on Biomedical Engineering
Article . 2015 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Seismocardiography-Based Detection of Cardiac Quiescence

Authors: Carson A. Wick; Omer T. Inan; James H. McClellan; Srini Tridandapani;

Seismocardiography-Based Detection of Cardiac Quiescence

Abstract

Cardiac-computed tomography angiography (CTA) is a minimally invasive imaging technology for characterizing coronary arteries. A fundamental limitation of CTA imaging is cardiac movement, which can cause artifacts and reduce the quality of the obtained images. To mitigate this problem, current approaches involve gating the image based on the electrocardiogram (ECG) to predict the timing of quiescent periods of the cardiac cycle. This paper focuses on developing a foundation for using a mechanical alternative to the ECG for finding these quiescent periods: the seismocardiogram (SCG). SCG was used to determine beat-by-beat systolic and diastolic quiescent periods of the cardiac cycle for nine healthy subjects, and 11 subjects with various cardiovascular diseases. To reduce noise in the SCG, and quantify these quiescent periods, a Kalman filter was designed to extract the velocity of chest wall movement from the recorded SCG signals. The average systolic and diastolic quiescent periods were centered at 29% and 76% for the healthy subjects, and 33% and 79% for subjects with cardiovascular disease. Both inter and intrasubject variability in the quiescent phases were observed compared to ECG-predicted phases, suggesting that the ECG may be a suboptimal modality for predicting quiescence, and that the SCG provides complementary data to the ECG.

Related Organizations
Keywords

Electrocardiography, Heart Diseases, Humans, Blood Pressure, Heart, Signal Processing, Computer-Assisted, Coronary Angiography, Algorithms

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Average
Top 10%
Top 10%
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