NDLI: Cardiac output and stroke volume estimation using a hybrid of three Windkessel models

Content Provider	IEEE Xplore Digital Library
Author	Arai, T. Kichang Lee Cohen, R.J.
Copyright Year	2010
Description	Author affiliation: Harvard-MIT Division of Health Sciences and Technology, 77 Massachusetts Avenue, Cambridge, 02139 USA (Kichang Lee; Cohen, R.J.) \|\| Department of Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT), Cambridge, 02139 USA (Arai, T.)
Abstract	Cardiac output (CO) and stroke volume (SV) are the key hemodynamic parameters to be monitored and assessed in ambulatory and critically ill patients. The purpose of this study was to introduce and validate a new algorithm to continuously estimate, within a proportionality constant, CO and SV by means of mathematical analysis of peripheral arterial blood pressure (ABP) waveforms. The algorithm combines three variants of the Windkessel model. Input parameters to the algorithm are the end-diastolic pressure, mean arterial pressures, inter-beat interval, and the time interval from end-diastolic to peak systolic pressure. The SV estimates from the three variants of the Windkessel model were weighted and integrated to provide beat-to-beat SV estimation. In order to validate the new algorithm, the estimated CO and SV were compared to those obtained through surgically implanted Transonic™ aortic flow probes placed around the aortic roots of six Yorkshire swine. Overall, estimation errors in CO and SV derived from radial ABP were 10.1% and 14.5% respectively, and 12.7% and 16.5% from femoral ABP. The new algorithm demonstrated statistically significant improvement in SV estimation compared with previous methods.
Starting Page	4971
Ending Page	4974
File Size	406911
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5627225
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation Algorithm design and analysis Time measurement Blood pressure Monitoring Extraterrestrial measurements Biomedical monitoring
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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