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    Rights statement: Copyright 2003 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/10.1117/12.497056

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Cardiovascular oscillations: in search of a nonlinear parametric model

Research output: Contribution to Journal/Magazine › Journal article

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Cardiovascular oscillations: in search of a nonlinear parametric model. / Bandrivskyy, Andriy; Luchinsky, Dmitry; McClintock, Peter V. E. et al.
In: Proceedings of SPIE, Vol. 5110, 30.04.2003, p. 271-281.

Research output: Contribution to Journal/Magazine › Journal article

Harvard

Bandrivskyy, A, Luchinsky, D, McClintock, PVE, Smelyanskiy, V, Stefanovska, A & Timucin, D 2003, 'Cardiovascular oscillations: in search of a nonlinear parametric model', Proceedings of SPIE, vol. 5110, pp. 271-281. https://doi.org/10.1117/12.497056

APA

Bandrivskyy, A., Luchinsky, D., McClintock, P. V. E., Smelyanskiy, V., Stefanovska, A., & Timucin, D. (2003). Cardiovascular oscillations: in search of a nonlinear parametric model. Proceedings of SPIE, 5110, 271-281. https://doi.org/10.1117/12.497056

Vancouver

Bandrivskyy A, Luchinsky D, McClintock PVE, Smelyanskiy V, Stefanovska A, Timucin D. Cardiovascular oscillations: in search of a nonlinear parametric model. Proceedings of SPIE. 2003 Apr 30;5110:271-281. doi: 10.1117/12.497056

Author

Bandrivskyy, Andriy ; Luchinsky, Dmitry ; McClintock, Peter V. E. et al. / Cardiovascular oscillations : in search of a nonlinear parametric model. In: Proceedings of SPIE. 2003 ; Vol. 5110. pp. 271-281.

Bibtex

@article{d9308e589d9a43c38697af55d1980928,
title = "Cardiovascular oscillations: in search of a nonlinear parametric model",
abstract = "We suggest a fresh approach to the modeling of the human cardiovascular system. Taking advantage of a new Bayesian inference technique, able to deal with stochastic nonlinear systems, we show that one can estimate parameters for models of the cardiovascular system directly from measured time series. We present preliminary results of inference of parameters of a model of coupled oscillators from measured cardiovascular data addressing cardiorespiratory interaction. We argue that the inference technique offers a very promising tool for the modeling, able to contribute significantly towards the solution of a long standing challenge -- development of new diagnostic techniques based on noninvasive measurements.",
author = "Andriy Bandrivskyy and Dmitry Luchinsky and McClintock, {Peter V. E.} and Vadim Smelyanskiy and Aneta Stefanovska and Dogan Timucin",
note = "Copyright 2003 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/10.1117/12.497056",
year = "2003",
month = apr,
day = "30",
doi = "10.1117/12.497056",
language = "English",
volume = "5110",
pages = "271--281",
journal = "Proceedings of SPIE",
issn = "0277-786X",
publisher = "SPIE",

}

RIS

TY - JOUR

T1 - Cardiovascular oscillations

T2 - in search of a nonlinear parametric model

AU - Bandrivskyy, Andriy

AU - Luchinsky, Dmitry

AU - McClintock, Peter V. E.

AU - Smelyanskiy, Vadim

AU - Stefanovska, Aneta

AU - Timucin, Dogan

N1 - Copyright 2003 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/10.1117/12.497056

PY - 2003/4/30

Y1 - 2003/4/30

N2 - We suggest a fresh approach to the modeling of the human cardiovascular system. Taking advantage of a new Bayesian inference technique, able to deal with stochastic nonlinear systems, we show that one can estimate parameters for models of the cardiovascular system directly from measured time series. We present preliminary results of inference of parameters of a model of coupled oscillators from measured cardiovascular data addressing cardiorespiratory interaction. We argue that the inference technique offers a very promising tool for the modeling, able to contribute significantly towards the solution of a long standing challenge -- development of new diagnostic techniques based on noninvasive measurements.

AB - We suggest a fresh approach to the modeling of the human cardiovascular system. Taking advantage of a new Bayesian inference technique, able to deal with stochastic nonlinear systems, we show that one can estimate parameters for models of the cardiovascular system directly from measured time series. We present preliminary results of inference of parameters of a model of coupled oscillators from measured cardiovascular data addressing cardiorespiratory interaction. We argue that the inference technique offers a very promising tool for the modeling, able to contribute significantly towards the solution of a long standing challenge -- development of new diagnostic techniques based on noninvasive measurements.

U2 - 10.1117/12.497056

DO - 10.1117/12.497056

M3 - Journal article

VL - 5110

SP - 271

EP - 281

JO - Proceedings of SPIE

JF - Proceedings of SPIE

SN - 0277-786X

ER -