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Blind identification of two-channel IIR systems with application to central cardiovascular monitoring / Jin-Oh Hahn in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 131 N° 5 (Septembre 2009) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 5 (Septembre 2009) . - 15 p. Titre : Blind identification of two-channel IIR systems with application to central cardiovascular monitoring Type de document : texte imprimé Auteurs : Jin-Oh Hahn, Auteur ; Andrew T. Reisner, Auteur ; Harry Asada, H., Auteur Année de publication : 2009 Article en page(s) : 15 p. Note générale : dynamic systems Langues : Anglais (eng) Mots-clés : two-channel  infinite  impulse  response  systems;  blind  identifiability;  input  signal  deconvolution  algorithm Résumé : This paper presents a new approach to blind identification of a class of two-channel infinite impulse response (IIR) systems with applicability to clinical cardiovascular monitoring. Specifically, this paper deals with a class of two-channel IIR systems describing wave propagation dynamics. For this class of systems, this paper first derives a blind identifiability condition and develops a blind identification algorithm, which is able to determine both the numerator and denominator polynomials of the channel dynamics uniquely. This paper also develops a new input signal deconvolution algorithm that can reconstruct the input signal from the identified two-channel dynamics and the associated two-channel measurements. These methods are applied to identify the pressure wave propagation dynamics in the cardiovascular system and reconstruct the aortic blood pressure and flow signals from blood pressure measurements taken at two distinct extremity locations. Persistent excitation, model identifiability, and asymptotic variance are analyzed to quantify the method’s validity, accuracy, and reliability without employing direct measurement of the aortic blood pressure and flow signals. The experimental results based on 83 data segments obtained from a swine subject illustrate how the cardiovascular dynamics can be identified accurately and reliably, and the aortic blood pressure and flow signals can be stably reconstructed from two distinct peripheral blood pressure signals under diverse physiologic conditions. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/Issue.aspx?issueID=26502&di [...] [article] Blind identification of two-channel IIR systems with application to central cardiovascular monitoring [texte imprimé] / Jin-Oh Hahn, Auteur ; Andrew T. Reisner, Auteur ; Harry Asada, H., Auteur . - 2009 . - 15 p. dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 5 (Septembre 2009) . - 15 p. Mots-clés : two-channel  infinite  impulse  response  systems;  blind  identifiability;  input  signal  deconvolution  algorithm Résumé : This paper presents a new approach to blind identification of a class of two-channel infinite impulse response (IIR) systems with applicability to clinical cardiovascular monitoring. Specifically, this paper deals with a class of two-channel IIR systems describing wave propagation dynamics. For this class of systems, this paper first derives a blind identifiability condition and develops a blind identification algorithm, which is able to determine both the numerator and denominator polynomials of the channel dynamics uniquely. This paper also develops a new input signal deconvolution algorithm that can reconstruct the input signal from the identified two-channel dynamics and the associated two-channel measurements. These methods are applied to identify the pressure wave propagation dynamics in the cardiovascular system and reconstruct the aortic blood pressure and flow signals from blood pressure measurements taken at two distinct extremity locations. Persistent excitation, model identifiability, and asymptotic variance are analyzed to quantify the method’s validity, accuracy, and reliability without employing direct measurement of the aortic blood pressure and flow signals. The experimental results based on 83 data segments obtained from a swine subject illustrate how the cardiovascular dynamics can be identified accurately and reliably, and the aortic blood pressure and flow signals can be stably reconstructed from two distinct peripheral blood pressure signals under diverse physiologic conditions. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/Issue.aspx?issueID=26502&di [...]

Identification of multichannel cardiovascular dynamics using dual laguerre basis functions for noninvasive cardiovascular monitoring / Jin-Oh Hahn in IEEE Transactions on control systems technology, Vol. 18 N° 1 (Janvier 2010) 

Public ISBD [article]  in IEEE Transactions on control systems technology > Vol. 18 N° 1 (Janvier 2010) . - pp. 170-176 Titre : Identification of multichannel cardiovascular dynamics using dual laguerre basis functions for noninvasive cardiovascular monitoring Type de document : texte imprimé Auteurs : Jin-Oh Hahn, Auteur ; Devin B. McCombie, Auteur ; Andrew T. Reisner, Auteur Année de publication : 2011 Article en page(s) : pp. 170-176 Note générale : Génie Aérospatial Langues : Anglais (eng) Mots-clés : Cardiovascular  (CV)  system  Laguerre  basis  function  Nonivasive  CV  monitoring  Two-channel  blind  system  identification  (ID) Index. décimale : 629.1 Résumé : This paper presents a novel method to identify the cardiovascular (CV) system using two distinct peripheral blood pressure (BP) signals. The method can characterize the distinct arterial path dynamics that shape each of the BP signals and recover the common central-flow signal fed to them. A Laguerre series data-compression technique is used to obtain a compact representation of the CV system, whose coefficients are identified using the multichannel blind system identification. A Laguerre model deconvolution algorithm is developed to stably recover the central-flow signal. Persistent excitation, model identifiability, and asymptotic variance are analyzed to quantify the method's validity and reliability, without using any direct measurement of central-flow input signal. Experimental results based on 7000 data segments obtained from nine swine subjects show that, for all the swine subjects under diverse physiologic conditions, the CV dynamics can be identified very reliably and the waveform of the central flow can be recovered stably from peripheral BP signals. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4815388 [article] Identification of multichannel cardiovascular dynamics using dual laguerre basis functions for noninvasive cardiovascular monitoring [texte imprimé] / Jin-Oh Hahn, Auteur ; Devin B. McCombie, Auteur ; Andrew T. Reisner, Auteur . - 2011 . - pp. 170-176. Génie Aérospatial Langues : Anglais (eng) in IEEE Transactions on control systems technology > Vol. 18 N° 1 (Janvier 2010) . - pp. 170-176 Mots-clés : Cardiovascular  (CV)  system  Laguerre  basis  function  Nonivasive  CV  monitoring  Two-channel  blind  system  identification  (ID) Index. décimale : 629.1 Résumé : This paper presents a novel method to identify the cardiovascular (CV) system using two distinct peripheral blood pressure (BP) signals. The method can characterize the distinct arterial path dynamics that shape each of the BP signals and recover the common central-flow signal fed to them. A Laguerre series data-compression technique is used to obtain a compact representation of the CV system, whose coefficients are identified using the multichannel blind system identification. A Laguerre model deconvolution algorithm is developed to stably recover the central-flow signal. Persistent excitation, model identifiability, and asymptotic variance are analyzed to quantify the method's validity and reliability, without using any direct measurement of central-flow input signal. Experimental results based on 7000 data segments obtained from nine swine subjects show that, for all the swine subjects under diverse physiologic conditions, the CV dynamics can be identified very reliably and the waveform of the central flow can be recovered stably from peripheral BP signals. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4815388