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Article
Peer-Review Record

Influence of the Tikhonov Regularization Parameter on the Accuracy of the Inverse Problem in Electrocardiography

Sensors 2023, 23(4), 1841; https://doi.org/10.3390/s23041841
by Tiantian Wang, Joël Karel, Pietro Bonizzi * and Ralf L. M. Peeters
Reviewer 1:
Reviewer 2:
Sensors 2023, 23(4), 1841; https://doi.org/10.3390/s23041841
Submission received: 13 December 2022 / Revised: 4 February 2023 / Accepted: 6 February 2023 / Published: 7 February 2023
(This article belongs to the Special Issue AI for Biomedical Sensing and Imaging)

Round 1

Reviewer 1 Report

This investigates the influence of the regularization parameter on the accuracy of the reconstruction of heart surface potentials, by assessing reconstruction accuracy with high-precision simultaneous heart and torso recordings from four dogs. This research has certain significance, but at present there are the following shortcomings.

1.     Several grammar errors/typo/spell errors throughout, need a critical language check. Most importantly, irregular usage of uppercase letters in the mid of the sentences

2.     The font of the symbols in the formula needs to be carefully checked and kept consistent.

3.       What is the significance of this work? What are the potential applications?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

1. Paper focus on an interesting topic of study.

2. Organization of the paper is good and accepted.

3. Theoretical background, basics, equations are well explained.

4. Comparative results presented validate the proposed framework.

5. The novelty of the paper is sound which is highlighted with good number of references. However, I would further elaborate on typical applications and improve the motivation in the abstract and introduction. Currently, the paper is "dry" and lacks a wider context.

 

6. References are up to date and properly cited as well.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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