Literature DB >> 22255630

A dynamical model for generating synthetic Phonocardiogram signals.

Ali Almasi1, Mohammad B Shamsollahi, Lotfi Senhadji.   

Abstract

In this paper we introduce a dynamical model for Phonocardiogram (PCG) signal which is capable of generating realistic synthetic PCG signals. This model is based on PCG morphology and consists of three ordinary differential equations and can represent various morphologies of normal PCG signals. Beat-to-beat variation in PCG morphology is significant so model parameters vary from beat to beat. This model is inspired of Electrocardiogram (ECG) dynamical model proposed by McSharry et al. and can be employed to assess biomedical signal processing techniques.

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Year:  2011        PMID: 22255630      PMCID: PMC3390312          DOI: 10.1109/IEMBS.2011.6091376

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  10 in total

1.  Extraction of the aortic and pulmonary components of the second heart sound using a nonlinear transient chirp signal model.

Authors:  J Xu; L G Durand; P Pibarot
Journal:  IEEE Trans Biomed Eng       Date:  2001-03       Impact factor: 4.538

2.  Nonlinear transient chirp signal modeling of the aortic and pulmonary components of the second heart sound.

Authors:  J Xu; L G Durand; P Pibarot
Journal:  IEEE Trans Biomed Eng       Date:  2000-10       Impact factor: 4.538

3.  A dynamical model for generating synthetic electrocardiogram signals.

Authors:  Patrick E McSharry; Gari D Clifford; Lionel Tarassenko; Leonard A Smith
Journal:  IEEE Trans Biomed Eng       Date:  2003-03       Impact factor: 4.538

4.  Synthetic ECG generation and Bayesian filtering using a Gaussian wave-based dynamical model.

Authors:  Omid Sayadi; Mohammad B Shamsollahi; Gari D Clifford
Journal:  Physiol Meas       Date:  2010-08-18       Impact factor: 2.833

5.  A model-based Bayesian framework for ECG beat segmentation.

Authors:  O Sayadi; M B Shamsollahi
Journal:  Physiol Meas       Date:  2009-02-25       Impact factor: 2.833

6.  ECG denoising and compression using a modified extended Kalman filter structure.

Authors:  Omid Sayadi; Mohammad Bagher Shamsollahi
Journal:  IEEE Trans Biomed Eng       Date:  2008-09       Impact factor: 4.538

7.  A nonlinear Bayesian filtering framework for ECG denoising.

Authors:  Reza Sameni; Mohammad B Shamsollahi; Christian Jutten; Gari D Clifford
Journal:  IEEE Trans Biomed Eng       Date:  2007-12       Impact factor: 4.538

8.  Analysis-synthesis of the phonocardiogram based on the matching pursuit method.

Authors:  X Zhang; L G Durand; L Senhadji; H C Lee; J L Coatrieux
Journal:  IEEE Trans Biomed Eng       Date:  1998-08       Impact factor: 4.538

9.  Time-frequency analysis of the first heart sound. Part 1: Simulation and analysis.

Authors:  D Chen; L G Durand; H C Lee
Journal:  Med Biol Eng Comput       Date:  1997-07       Impact factor: 2.602

10.  Analysis of the first heart sound using the matching pursuit method.

Authors:  W Wang; Z Guo; J Yang; Y Zhang; L G Durand; M Loew
Journal:  Med Biol Eng Comput       Date:  2001-11       Impact factor: 3.079

  10 in total
  2 in total

1.  Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms.

Authors:  Radek Martinek; Radana Kahankova; Homer Nazeran; Jaromir Konecny; Janusz Jezewski; Petr Janku; Petr Bilik; Jan Zidek; Jan Nedoma; Marcel Fajkus
Journal:  Sensors (Basel)       Date:  2017-05-19       Impact factor: 3.576

2.  A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring.

Authors:  Radek Martinek; Jan Nedoma; Marcel Fajkus; Radana Kahankova; Jaromir Konecny; Petr Janku; Stanislav Kepak; Petr Bilik; Homer Nazeran
Journal:  Sensors (Basel)       Date:  2017-04-18       Impact factor: 3.576

  2 in total

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