ECG signal reconstruction based on stochastic joint-modelling of the ECG and the PPG signals

D. Martín-Martínez, P. Casaseca-de-la-Higuera, M. Martín-Fernández, C. Alberola-López

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this paper, we propose a model-based methodology aimed at reconstructing corrupted or missing intervals of ECG signals acquired together with a PPG signal. To this end, we first estimate a joint-model of the ECG and PPG signals from the largest uncorrupted piece. Then, in a second stage, a set of candidates to replace the corrupted epoch is synthesized by sampling the aforementioned model. Each sample is evaluated respect to a boundary condition in order to select the best candidate. This signal is refined through an iterative method relying on the actual PPG data acquired during the corruption interval. Experiments on real data, show the capability of the proposed methodology to accurately reconstruct ECG pieces, outperforming so far presented solutions not accounting for joint information.
Original languageEnglish
Title of host publicationXIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013
Subtitle of host publicationMEDICON 2013, 25-28 September 2013, Seville, Spain
EditorsLaura M. Roa Romero
PublisherSpringer International Publishing AG
Pages989-992
Number of pages4
Volume41
ISBN (Electronic)9783319008462
ISBN (Print)9783319008455
DOIs
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameIFMBE Proceedings
PublisherSpringer
Volume41
ISSN (Print)1680-0737
ISSN (Electronic)1433-9277

Keywords

  • ECG reconstruction
  • joint ECG-PPG modeling
  • waveform model
  • evolution model
  • ARMA
  • PCA

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