Statistical Estimation Applied to Electrocardiographic Imaging

This paper presents a method to solve a linear regression problem subject to group lasso and ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or frame. The optimisation algorithm was performed using the block coordinate descent and proximal gradient descent methods. The explicit computation of the underlying Kronecker structure in the regression was avoided, reducing space and temporal complexity. We developed an algorithm that supports the use of arbitrary dictionaries to obtain solutions and allows a flexible group distribution.

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“…At the internal loop involved in the APGM, we compute the total residue r int recursively to evaluate the gradient (13).…”

Section: Internal Loopmentioning

confidence: 99%

“…However, ECGI regularisation methods can be formulated from a statistical perspective [12,13]. These schemes allow the inclusion of prior information from training sets of either simulated or real data.…”

Section: Introductionmentioning

confidence: 99%

A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging

Caracciolo¹,

Caiafa²,

Pería³

et al. 2022

Biomed. Phys. Eng. Express

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The Importance of ECG Offset Correction for Premature Ventricular Contraction Origin Localization from Clinical Data

Svehlikova

Přibilová

Zelinka

et al. 2022

Measurement Science Review

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In this study, the inverse solution with a single dipole was computed to localize the premature ventricular contraction (PVC) origin from long term multiple leads ECG measurements on fourteen patients. The stability of the obtained results was studied with respect to the preprocessing of signals used as an input to the inverse solution and the complexity of the torso model. Two methods were used for the baseline drift removal. After an averaging of the heartbeats, the influence of the retention or elimination of the remaining offset at the beginning of the PVC signal was examined. The inverse computations were performed using both homogeneous and inhomogeneous patient-specific torso models. It was shown that the remaining offset in the averaged signals at the beginning of the PVC signal had the most significant impact on the stability of the resulting position within the ventricles. Its elimination stabilizes the location of the results, decreases the sensitivity to the torso model complexity and decreases the sensitivity to the primary baseline drift removal method. The additional offset correction decreased the mean distance between the results for all patients from 17-18 mm to 1-2 mm, regardless of the baseline drift removal method or the torso model complexity.

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Statistical Estimation Applied to Electrocardiographic Imaging

Cited by 2 publications

References 36 publications

A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging

A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging

The Importance of ECG Offset Correction for Premature Ventricular Contraction Origin Localization from Clinical Data

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