Detail publikace

In-vivo and Isolated HRV Analysis by Hidden Markov Model

JANOUŠEK, O. RONZHINA, M. KOLÁŘOVÁ, J. PROVAZNÍK, I. NOVÁKOVÁ, M. SCHEER, P.

Originální název

In-vivo and Isolated HRV Analysis by Hidden Markov Model

Český název

In-vivo and Isolated HRV Analysis by Hidden Markov Model

Anglický název

In-vivo and Isolated HRV Analysis by Hidden Markov Model

Typ

článek ve sborníku

Jazyk

en

Originální abstrakt

Analysis of details of heart rate variability (HRV) series may improve diagnosis of nervous system activity. The aim of this study was to quantify oscillation character in HRV series details with usage of Hidden Markov model (HMM). Five New Zealand white rabbits and five isolated New Zealand rabbit hearts at Langendorff setup were studied. All oscillation-related coefficients of HMM transient matrix were significantly lower in isolated heart HRV series than in in-vivo ones. Significant tendency to compensate immediately the changes in RR interval duration is characteristic for isolated heart. Compensation process is very prompt, based on only one previous RR interval.

Český abstrakt

Analysis of details of heart rate variability (HRV) series may improve diagnosis of nervous system activity. The aim of this study was to quantify oscillation character in HRV series details with usage of Hidden Markov model (HMM). Five New Zealand white rabbits and five isolated New Zealand rabbit hearts at Langendorff setup were studied. All oscillation-related coefficients of HMM transient matrix were significantly lower in isolated heart HRV series than in in-vivo ones. Significant tendency to compensate immediately the changes in RR interval duration is characteristic for isolated heart. Compensation process is very prompt, based on only one previous RR interval.

Anglický abstrakt

Analysis of details of heart rate variability (HRV) series may improve diagnosis of nervous system activity. The aim of this study was to quantify oscillation character in HRV series details with usage of Hidden Markov model (HMM). Five New Zealand white rabbits and five isolated New Zealand rabbit hearts at Langendorff setup were studied. All oscillation-related coefficients of HMM transient matrix were significantly lower in isolated heart HRV series than in in-vivo ones. Significant tendency to compensate immediately the changes in RR interval duration is characteristic for isolated heart. Compensation process is very prompt, based on only one previous RR interval.

Klíčová slova

HMM, isolated rabbit heart, HRV

Rok RIV

2014

Vydáno

27.11.2014

Nakladatel

Computing in Cardiology 2014

Místo

Cambridge, USA

ISBN

978-1-4799-4347-0

Kniha

Computing in Cardiology 2014

Edice

41

Číslo edice

1

Strany od

981

Strany do

984

Strany počet

4

URL

BibTex


@inproceedings{BUT110232,
  author="Oto {Janoušek} and Marina {Ronzhina} and Jana {Kolářová} and Ivo {Provazník} and Marie {Nováková} and Peter {Scheer}",
  title="In-vivo and Isolated HRV Analysis by Hidden Markov Model",
  annote="Analysis of details of heart rate variability (HRV) series may improve diagnosis of nervous system activity. The aim of this study was to quantify oscillation character in HRV series details with usage of Hidden Markov model (HMM). 
Five New Zealand white rabbits and five isolated New Zealand rabbit hearts at Langendorff setup were studied. All oscillation-related coefficients of HMM transient matrix were significantly lower in isolated heart HRV series than in in-vivo ones. Significant tendency to compensate immediately the changes in RR interval duration is characteristic for isolated heart. Compensation process is very prompt, based on only one previous RR interval.",
  address="Computing in Cardiology 2014",
  booktitle="Computing in Cardiology 2014",
  chapter="110232",
  edition="41",
  howpublished="online",
  institution="Computing in Cardiology 2014",
  year="2014",
  month="november",
  pages="981--984",
  publisher="Computing in Cardiology 2014",
  type="conference paper"
}