Literature DB >> 12669990

Analysis of heart rate variability in the presence of ectopic beats using the heart timing signal.

Javier Mateo1, Pablo Laguna.   

Abstract

The time-domain signals representing the heart rate variability (HRV) in the presence of an ectopic beat exhibit a sharp transient at the position of the ectopic beat, which corrupts the signal, particularly the power spectral density (PSD) of the HRV. Consequently, there is a need for correction of this type of beat prior to any HRV analysis. This paper deals with the PSD estimation of the HRV by means of the heart timing (HT) signal when ectopic beats are present. These beat occurrence times are modeled from a generalized, continuous time integral pulse frequency modulation model and, from this point of view, a specific method for minimizing the effect of the presence of ectopic beats is presented to work together with the HT signal. By using both, a white noise driven autoregressive model of the HRV signal with artificially introduced ectopic beats and actual heart rate series including ectopic beats, the more usual methods of HRV spectral estimation are compared. Results of the PSD estimation error function of the number of ectopic beats are presented. These results demonstrate that the proposed method has one order of magnitude lower error than usual ectopic beats removal strategies in preserving PSD, thus, this strategy better recovers the original clinical indexes of interest.

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Year:  2003        PMID: 12669990     DOI: 10.1109/TBME.2003.808831

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  34 in total

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Authors:  Feng Wen; Fang-Tian He
Journal:  J Zhejiang Univ Sci B       Date:  2011-12       Impact factor: 3.066

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Journal:  Med Biol Eng Comput       Date:  2010-03-19       Impact factor: 2.602

3.  Using a Calculated Pulse Rate with an Artificial Neural Network to Detect Irregular Interbeats.

Authors:  Bih-Chyun Yeh; Wen-Piao Lin
Journal:  J Med Syst       Date:  2015-12-07       Impact factor: 4.460

4.  Drowsiness detection using heart rate variability.

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Journal:  Med Biol Eng Comput       Date:  2016-01-16       Impact factor: 2.602

5.  Quantifying the lagged Poincaré plot geometry of ultrashort heart rate variability series: automatic recognition of odor hedonic tone.

Authors:  M Nardelli; G Valenza; A Greco; A Lanatá; E P Scilingo; R Bailón
Journal:  Med Biol Eng Comput       Date:  2020-03-11       Impact factor: 2.602

6.  Do the deceleration/acceleration capacities of heart rate reflect cardiac sympathetic or vagal activity? A model study.

Authors:  Qing Pan; Gongzhan Zhou; Ruofan Wang; Guolong Cai; Jing Yan; Luping Fang; Gangmin Ning
Journal:  Med Biol Eng Comput       Date:  2016-04-08       Impact factor: 2.602

7.  A real-time automated point-process method for the detection and correction of erroneous and ectopic heartbeats.

Authors:  Luca Citi; Emery N Brown; Riccardo Barbieri
Journal:  IEEE Trans Biomed Eng       Date:  2012-08-02       Impact factor: 4.538

8.  Methodological framework for heart rate variability analysis during exercise: application to running and cycling stress testing.

Authors:  David Hernando; Alberto Hernando; Jose A Casajús; Pablo Laguna; Nuria Garatachea; Raquel Bailón
Journal:  Med Biol Eng Comput       Date:  2017-09-26       Impact factor: 2.602

9.  The sensitivity of 38 heart rate variability measures to the addition of artifact in human and artificial 24-hr cardiac recordings.

Authors:  Nicolas J C Stapelberg; David L Neumann; David H K Shum; Harry McConnell; Ian Hamilton-Craig
Journal:  Ann Noninvasive Electrocardiol       Date:  2017-07-02       Impact factor: 1.468

10.  Can accelerometry data improve estimates of heart rate variability from wrist pulse PPG sensors?

Authors:  Maciej Kos; Iman Khaghani-Far; Christine M Gordon; Misha Pavel; Holly B Jimison
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2017-07
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