This paper presents a model-based blind system identification approach to estimation of central aortic blood pressure (BP) waveform from noninvasive diametric circulatory signals. First, we developed a mathematical model to reproduce the relationship between central aortic BP waveform and a class of noninvasive circulatory signals at diametric locations by combining models to represent wave propagation in the artery, arterial pressure–volume relationship, and mechanics of the measurement instrument. Second, we formulated the problem of estimating central aortic BP waveform from noninvasive diametric circulatory signals into a blind system identification problem. Third, we performed identifiability analysis to show that the mathematical model could be identified and its parameters determined up to an unknown scale. Finally, we illustrated the feasibility of the approach by applying it to estimate central aortic BP waveform from two diametric pulse volume recording (PVR) signals. Experimental results from ten human subjects showed that the proposed approach could estimate central aortic BP waveform accurately: the average root-mean-squared error (RMSE) associated with the central aortic BP waveform was 4.1 mm Hg (amounting to 4.5% of the underlying mean BP) while the average errors associated with central aortic systolic pressure (SP) and pulse pressure (PP) were 2.4 mm Hg and 2.0 mm Hg (amounting to 2.5% and 2.1% of the underlying mean BP). The proposed approach may contribute to the improved monitoring of cardiovascular (CV) health by enabling estimation of central aortic BP waveform from conveniently measurable diametric circulatory signals.
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June 2017
Research-Article
Model-Based Blind System Identification Approach to Estimation of Central Aortic Blood Pressure Waveform From Noninvasive Diametric Circulatory Signals
Zahra Ghasemi,
Zahra Ghasemi
Department of Mechanical Engineering,
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: zghasemi@umd.edu
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: zghasemi@umd.edu
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Chang-Sei Kim,
Chang-Sei Kim
Department of Mechanical Engineering,
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: cskim75@umd.edu
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: cskim75@umd.edu
Search for other works by this author on:
Eric Ginsberg,
Eric Ginsberg
Department of Medicine,
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: eginsberg@medicine.umaryland.edu
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: eginsberg@medicine.umaryland.edu
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Anuj Gupta,
Anuj Gupta
Department of Medicine,
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: agupta@medicine.umaryland.edu
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: agupta@medicine.umaryland.edu
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Jin-Oh Hahn
Jin-Oh Hahn
Mem. ASME
Department of Mechanical Engineering,
University of Maryland,
2181 Glenn L. Martin Hall,
College Park, MD 20742
e-mail: Jhahn12@umd.edu
Department of Mechanical Engineering,
University of Maryland,
2181 Glenn L. Martin Hall,
College Park, MD 20742
e-mail: Jhahn12@umd.edu
Search for other works by this author on:
Zahra Ghasemi
Department of Mechanical Engineering,
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: zghasemi@umd.edu
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: zghasemi@umd.edu
Chang-Sei Kim
Department of Mechanical Engineering,
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: cskim75@umd.edu
University of Maryland,
2107B Glenn L. Martin Hall,
College Park, MD 20742
e-mail: cskim75@umd.edu
Eric Ginsberg
Department of Medicine,
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: eginsberg@medicine.umaryland.edu
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: eginsberg@medicine.umaryland.edu
Anuj Gupta
Department of Medicine,
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: agupta@medicine.umaryland.edu
University of Maryland Medical Center,
110 South Paca Street, 7th Floor, Cardiology,
Baltimore, MD 21201
e-mail: agupta@medicine.umaryland.edu
Jin-Oh Hahn
Mem. ASME
Department of Mechanical Engineering,
University of Maryland,
2181 Glenn L. Martin Hall,
College Park, MD 20742
e-mail: Jhahn12@umd.edu
Department of Mechanical Engineering,
University of Maryland,
2181 Glenn L. Martin Hall,
College Park, MD 20742
e-mail: Jhahn12@umd.edu
1Corresponding author.
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received April 28, 2016; final manuscript received November 29, 2016; published online March 22, 2017. Assoc. Editor: Jongeun Choi.
J. Dyn. Sys., Meas., Control. Jun 2017, 139(6): 061003 (10 pages)
Published Online: March 22, 2017
Article history
Received:
April 28, 2016
Revised:
November 29, 2016
Citation
Ghasemi, Z., Kim, C., Ginsberg, E., Gupta, A., and Hahn, J. (March 22, 2017). "Model-Based Blind System Identification Approach to Estimation of Central Aortic Blood Pressure Waveform From Noninvasive Diametric Circulatory Signals." ASME. J. Dyn. Sys., Meas., Control. June 2017; 139(6): 061003. https://doi.org/10.1115/1.4035451
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