Biometric-Based Human Identification Using Ensemble-Based Technique and ECG Signals
, Yassine Daadaa 1, Imran Qureshi 1, Ganeshkumar Perumal 1, Mostafa E. A. Ibrahim 1,2 and Alaa E. S. Ahmed 1,3Round 1
Reviewer 1 Report
Fine
Comments for author File: 
Comments.pdf
Author Response
Original Manuscript ID: ID: applsci-2566817
Original Article Title: Biometric-based Human Identification using Ensemble-based Technique and ECG Signals
To: Editor in Chief,
MDPI, Applied Sciences
Re: Response to reviewers
Dear Editor,
Many thanks for insightful comments and suggestions of the referees. Thank you for allowing a resubmission of our manuscript, with an opportunity to address the reviewers’ comments.
We are uploading (a) our point-by-point response to the comments (below) (response to reviewers), (b) an updated manuscript with yellow highlighting indicating changes, and (c) a clean updated manuscript without highlights (PDF main document).
By following reviewers’ comments, we made substantial modifications in our paper to improve its clarity, English and readability. In our revised paper, we represent the improved manuscript such as:
(1) Revised Abstract, (2) Revised Introduction, (3) Results section, (4) Discussions and Conclusion sections.
We have made the following modifications as desired by the reviewers:
Best regards,
Corresponding Author,
Dr. Qaisar Abbas (On behalf of authors),
Professor.
Author Response File: Author Response.pdf
Reviewer 2 Report
In this paper, the authors investigate cardiac biometrics as a secure authentication method using deep learning approaches. Cardiac biometric systems utilize signals captured through ECG, PPG, and PCG. The primary focus of the study is on using ECG as a biometric modality for human identification. To optimize features, the authors develop an ensemble approach based on VGG16 pre-trained transfer learning and LSTM architectures. The paper is well-motivated and provides valuable insights into medical applications. Here are some suggestions for improving the paper:
1. Emphasize the rationale behind conducting research on biometric-based human identification in the abstract, which currently appears lengthy.
2. Create a comprehensive table summarizing the key abbreviations used in the paper to improve clarity.
3. Enrich the related works by incorporating recent review works on explainable AI in medicine, such as "Explainable AI in big data intelligence of community detection for digitalization e-healthcare services."
4. Provide time complexity analysis and computational cost analysis for the presented algorithms.
5. Consider redrawing figures with low resolution, such as Fig. 4, to enhance their quality and resolution.
Minor editing of English language required.
Author Response
Original Manuscript ID: ID: applsci-2566817
Original Article Title: Biometric-based Human Identification using Ensemble-based Technique and ECG Signals
To: Editor in Chief,
MDPI, Applied Sciences
Re: Response to reviewers
Dear Editor,
Many thanks for insightful comments and suggestions of the referees. Thank you for allowing a resubmission of our manuscript, with an opportunity to address the reviewers’ comments.
We are uploading (a) our point-by-point response to the comments (below) (response to reviewers), (b) an updated manuscript with yellow highlighting indicating changes, and (c) a clean updated manuscript without highlights (PDF main document).
By following reviewers’ comments, we made substantial modifications in our paper to improve its clarity, English and readability. In our revised paper, we represent the improved manuscript such as:
(1) Revised Abstract, (2) Revised Introduction, (3) Results section, (4) Discussions and Conclusion sections.
We have made the following modifications as desired by the reviewers:
Best regards,
Corresponding Author,
Dr. Qaisar Abbas (On behalf of authors),
Professor.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Thanks for re-submitting your article with all the requested modifications. I can see many improvements compared to the to the initial submission. I believe your article is ready for the next stage.
