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Content Provider | IEEE Xplore Digital Library |
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Author | Jin-Oh Hahn, Asada, H. Harry Reisner, Andrew T. Jaffer, Farouc A. |
Copyright Year | 2008 |
Description | Author affiliation: Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, 02139, USA (Jin-Oh Hahn,; Asada, H. Harry) || Department of Emergency Medicine, Massachusetts General Hospital, Boston, 02114, USA (Reisner, Andrew T.) || Department of Cardiovascular Medicine, Massachusetts General Hospital, Boston, 02114, USA (Jaffer, Farouc A.) |
Abstract | This paper presents a new system identification approach to the reconstruction of central aortic blood pressure signal by exploiting a non-invasive peripheral blood pressure measurement. This technique, which is called the “adaptive” transfer function, is able to reconstruct the aortic blood pressure signal by characterizing the aortic-to-peripheral cardiovascular dynamics solely based on the peripheral measurement. In contrast to the previous related efforts, it does not require any a priori knowledge on the empirical and/or population-based relationship, e.g. the predetermined or generalized transfer function, as well as multiple peripheral measurements. The initial proof-of-principle on the efficacy of the adaptive transfer function is demonstrated by the experimental results from human and animal subjects. |
Starting Page | 813 |
Ending Page | 816 |
File Size | 341927 |
Page Count | 4 |
File Format | |
ISBN | 9781424418145 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2008.4649278 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2008-08-20 |
Publisher Place | Canada |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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