Aortic Pressure Estimation Using Blind Identification Approach on Single Input Multiple Output Nonlinear Wiener Systems

Aortic pressure (P a ) is important for diagnosis of cardiovascular diseases, but it cannot be directly measured by noninvasive means. We present a method for its estimation by modeling arterial system as multichannel Weiner system with linear finite impulse response filter accounting for larger art...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2018-06, Vol.65 (6), p.1193-1200
Main Authors: Patel, Amit M., Li, John K-J., Finegan, Barry, McMurtry, Michael S.
Format: Article
Language:English
Subjects:
Aorta
Aortic pressure
arterial system model
Arteries
Biomedical measurement
Cardiovascular diseases
Finite impulse response filters
FIR filters
Heart diseases
Hemodynamics
Kernel
Mathematical model
Maximum likelihood detection
Nonlinear systems
Pressure
Pressure measurement
System dynamics
System identification
transfer function
Viscoelasticity
Waveforms
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Summary:Aortic pressure (P a ) is important for diagnosis of cardiovascular diseases, but it cannot be directly measured by noninvasive means. We present a method for its estimation by modeling arterial system as multichannel Weiner system with linear finite impulse response filter accounting for larger arteries transmission channel and nonlinear memoryless function block accounting for all nonlinearities due to narrowing of arteries, branching and visco-elastic forces. With this structure when pressure waveforms are measured from two distinct peripheral locations, multichannel blind system identification (MBSI) technique can be used to estimate common input pressure signal or P a . Nonlinear MBSI method was employed on previously acquired human hemodynamic measurements (seven datasets); results show P a can be accurately derived. This method by nature is self-calibrating to account for any interpersonal, along with intrapersonal, vascular dynamics inconstancy. Besides Pa estimation, the proposed MBSI method also allows extraction of system dynamics for vascular channels.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2017.2688425