Novel hybrid method for interpolating missing information in body surface potential maps

Rababah, Ali; Bond, Raymond; Rjoob, Khaled; Guldenring, Daniel; McLaughlin, James; Finlay, Dewar

doi:10.1016/j.jelectrocard.2019.09.003

Cited by 8 publications

(3 citation statements)

References 11 publications

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“…The problem of missing or small amplitude signals is being solved also in the Signal preprocessing group of the Consortium of Electrocardiographic Imaging. The novel method for interpolation of missing signals was introduced in [2]. The effect of the interpolation of ECG signals on the results of the inverse solution (ECG imaging) for various scenarios of omitted electrodes was studied in [3] and [4].…”

Section: Introductionmentioning

confidence: 99%

The Influence of the Most Powerful Signals on the Pacing Site Localization by Single Dipole

Svehlikova

Ondrusova

Zelinka

et al. 2020

2020 Computing in Cardiology Conference (CinC)

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In real experiments with body surface potential mapping, it is usual that the measuring electrodes cannot be placed regularly because of other patches of sensors used on the torso during the procedure. The influence of accidentally missing the most powerful ECG signals on the inverse localization of the pacing site using a single dipole was studied.Body surface potential maps from three tank experiments on the pig or dog heart and one measurement from the patient's torso were used for inverse computation of the known pacing site position using the full electrodes setup and setups omitting 10% and 20% of the signals with the largest power. The sensitivity of the inverse method was evaluated by localization error between the true and computed pacing site.The localization error did not change (13mm or 7mm) or changed from 13 to 24 mm for tank data, but it increased rapidly from 19 to 41/68 mm for human data.The largest effect of electrodes' omission using human data can be explained by the largest complexity of the human torso what is not fully included in the computational torso model.

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Section: Introductionmentioning

confidence: 99%

The Influence of the Most Powerful Signals on the Pacing Site Localization by Single Dipole

Svehlikova

Ondrusova

Zelinka

et al. 2020

2020 Computing in Cardiology Conference (CinC)

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“…Five different interpolation methods were used to reconstruct the missing leads: 1) Laplacian interpolation (LAP) (SCIRun: http://www.sci.utah.edu/cibcsoftware/scirun.html), 2) Inverse-distance square weighting (IDS) [7], 3) Kriging method (KRI) [8], 4) The inverseforward method (I-F) [3], 5) A hybrid method [9]. In the training step of this hybrid method, first only the first beat (HYB1), then the first 10 beats (HYB2), were used.…”

Section: Methodsmentioning

confidence: 99%

Effects of Interpolation on the Inverse Problem of Electrocardiography

Doğrusöz¹,

Bear²,

Bergquist³

et al. 2019

2019 Computing in Cardiology Conference (CinC)

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Electrocardiographic Imaging (ECGI) aims to reconstruct electrograms from the body surface potential measurements. Bad leads are usually excluded from the inverse problem solution. Alternatively, interpolation can be applied. This study explores how sensitive ECGI is to different bad-lead configurations and interpolation methods. Experimental data from a Langendorff-perfused pig heart suspended in a human-shaped torso-tank was used. Six different bad lead cases were designed based on clinical experience. Inverse problem was solved by applying Tikhonov regularization i) using the complete data, ii) badleads-removed data, and iii) interpolated data, with 5 different methods. Our results showed that ECGI accuracy of an interpolation method highly depends on the location of the bad leads. If they are in the high-potential-gradient regions of the torso, a highly accurate interpolation method is needed to achieve an ECGI accuracy close to using complete data. If the BSP reconstruction of the interpolation method is poor in these regions, the reconstructed electrograms also have lower accuracy, suggesting that bad leads should be removed instead of interpolated. The inverseforward method was found to be the best among all interpolation methods applied in this study in terms of both missing BSP lead reconstruction and ECGI accuracy, even for the bad leads located over the chest.

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“…For those samples with missing values, the commonly used processing methods are interpolation ( Liu et al, 1997 ; Rababah Msc et al, 2019 ), mean, mode, and median, and nearest neighbor imputation ( Beretta and Santaniello, 2016 ). Although nearest neighbor imputation has good performance in image processing, there are some limitations to this experiment because of the number of samples.…”

Section: Experiments Designmentioning

confidence: 99%

Intelligent assistant diagnosis for pediatric inguinal hernia based on a multilayer and unbalanced classification model

Liu

Chen²,

Dong³

et al. 2023

Front. Physiol.

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As one of the most common diseases in pediatric surgery, an inguinal hernia is usually diagnosed by medical experts based on clinical data collected from magnetic resonance imaging (MRI), computed tomography (CT), or B-ultrasound. The parameters of blood routine examination, such as white blood cell count and platelet count, are often used as diagnostic indicators of intestinal necrosis. Based on the medical numerical data on blood routine examination parameters and liver and kidney function parameters, this paper used machine learning algorithm to assist the diagnosis of intestinal necrosis in children with inguinal hernia before operation. In the work, we used clinical data consisting of 3,807 children with inguinal hernia symptoms and 170 children with intestinal necrosis and perforation caused by the disease. Three different models were constructed according to the blood routine examination and liver and kidney function. Some missing values were replaced by using the RIN-3M (median, mean, or mode region random interpolation) method according to the actual necessity, and the ensemble learning based on the voting principle was used to deal with the imbalanced datasets. The model trained after feature selection yielded satisfactory results with an accuracy of 86.43%, sensitivity of 84.34%, specificity of 96.89%, and AUC value of 0.91. Therefore, the proposed methods may be a potential idea for auxiliary diagnosis of inguinal hernia in children.

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Novel hybrid method for interpolating missing information in body surface potential maps

Cited by 8 publications

References 11 publications

The Influence of the Most Powerful Signals on the Pacing Site Localization by Single Dipole

The Influence of the Most Powerful Signals on the Pacing Site Localization by Single Dipole

Effects of Interpolation on the Inverse Problem of Electrocardiography

Intelligent assistant diagnosis for pediatric inguinal hernia based on a multilayer and unbalanced classification model

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