An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

Body surface potential maps (BSPMs) are typically recorded from a large number of ECG leads that cover the entire thorax. This improves diagnostic accuracy and is required in Electrocardiographic imaging (ECGi). BSPMs recorded in the clinical setting may have some leads that are noisy due to poor skin electrode contact. We analyzed 117 lead BSPMs recorded from 360 subjects. We successively simulated the removal of ECG leads at various locations and tested the ability of our algorithm to accurately reconstruct the missing information.
LanguageEnglish
Pages1
Number of pages4
Publication statusE-pub ahead of print - 1 Oct 2018
EventComputing in Cardiology - Maastricht, Netherlands
Duration: 23 Sep 201826 Sep 2018
http://www.cinc.org/2018/CinC2018ProgramOverview.pdf

Conference

ConferenceComputing in Cardiology
CountryNetherlands
CityMaastricht
Period23/09/1826/09/18
Internet address

Fingerprint

interpolation
skin
electrode
noise reduction
removal

Keywords

  • ECG
  • BSPM
  • Laplacian
  • Noise
  • Signal Processing

Cite this

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title = "An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps",
abstract = "Body surface potential maps (BSPMs) are typically recorded from a large number of ECG leads that cover the entire thorax. This improves diagnostic accuracy and is required in Electrocardiographic imaging (ECGi). BSPMs recorded in the clinical setting may have some leads that are noisy due to poor skin electrode contact. We analyzed 117 lead BSPMs recorded from 360 subjects. We successively simulated the removal of ECG leads at various locations and tested the ability of our algorithm to accurately reconstruct the missing information.",
keywords = "ECG, BSPM, Laplacian, Noise, Signal Processing",
author = "Ali Rababah and D Finlay and D Guldenring and RR Bond and James McLaughlin",
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language = "English",
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note = "Computing in Cardiology ; Conference date: 23-09-2018 Through 26-09-2018",
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Rababah, A, Finlay, D, Guldenring, D, Bond, RR & McLaughlin, J 2018, 'An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps' Paper presented at Computing in Cardiology, Maastricht, Netherlands, 23/09/18 - 26/09/18, pp. 1.

An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps. / Rababah, Ali; Finlay, D; Guldenring, D; Bond, RR; McLaughlin, James.

2018. 1 Paper presented at Computing in Cardiology, Maastricht, Netherlands.

Research output: Contribution to conferencePaper

TY - CONF

T1 - An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps

AU - Rababah, Ali

AU - Finlay, D

AU - Guldenring, D

AU - Bond, RR

AU - McLaughlin, James

PY - 2018/10/1

Y1 - 2018/10/1

N2 - Body surface potential maps (BSPMs) are typically recorded from a large number of ECG leads that cover the entire thorax. This improves diagnostic accuracy and is required in Electrocardiographic imaging (ECGi). BSPMs recorded in the clinical setting may have some leads that are noisy due to poor skin electrode contact. We analyzed 117 lead BSPMs recorded from 360 subjects. We successively simulated the removal of ECG leads at various locations and tested the ability of our algorithm to accurately reconstruct the missing information.

AB - Body surface potential maps (BSPMs) are typically recorded from a large number of ECG leads that cover the entire thorax. This improves diagnostic accuracy and is required in Electrocardiographic imaging (ECGi). BSPMs recorded in the clinical setting may have some leads that are noisy due to poor skin electrode contact. We analyzed 117 lead BSPMs recorded from 360 subjects. We successively simulated the removal of ECG leads at various locations and tested the ability of our algorithm to accurately reconstruct the missing information.

KW - ECG

KW - BSPM

KW - Laplacian

KW - Noise

KW - Signal Processing

UR - http://www.cinc2018.org/

M3 - Paper

SP - 1

ER -