PONE-D-25-29278Smartwatch-Based Detection of Loss of PulsePLOS ONE

Dear Dr. Demirel,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Two reviewers have provided their feedback below. Please address each point in turn. In particular, the reviewers ask for clarification in a number of areas and request that you check for consistent use of specific terminology.

Please submit your revised manuscript by Sep 04 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Joanna Tindall, PhD

Staff Editor

PLOS ONE

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5. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for this timely and important contribution. Your work introduces a novel dataset and framework for smartwatch-based detection of pulse loss. However, I have several important concerns and questions regarding the clarity and completeness of the methods, evaluation, and claims that need to be addressed.

1. Classification Labels and Evaluation Metrics

The paper states that the task is a three-class classification problem: pulse loss, normal operation, and idle (non-usage of smartwatch). However, Figure 4 and several parts of the text seem to only reference binary classification (e.g., "pulse" vs. "no pulse").

The metrics presented (sensitivity and specificity) are defined and reported in the binary classification context. Please clarify:

Are you performing binary or multiclass classification?

If multiclass, please provide per-class sensitivity and specificity, or macro- or weighted-averaged values for all classes.

Figure 4 and its caption should clearly show all 3 classes, if that’s the intention.

2. Terminology: "Deep Learning" vs. "Neural Network"

Throughout the manuscript, you refer to your deep learning model as a "neural network" and at times suggest it's an autoencoder. The current architecture more closely resembles a dual-encoder fusion model with LSTM layers, not an autoencoder.

Please revise the terminology to reflect the actual structure (e.g., “dual-stream CNN-LSTM” or “multi-modal encoder network”) to avoid confusion.

3. Proposed Method Identification

It is unclear which model is considered your proposed method: is it the deep learning architecture or one of the ensemble ML classifiers?

Please explicitly label the "proposed model" in the tables and main text and clearly distinguish between baseline comparisons and the final model.

4. Feature Dimensions and Signal Processing

You extracted features from all 3 IMU channels. Please clarify:

What is the final shape of the input feature vector to the classifiers?

Did you compute features for each axis individually and then concatenate them?

Or did you average features across the three axes before feeding to the model?

You state that no filtering or normalization was applied to IMU signals. Please justify this, especially since IMU signals tend to be noisy and scale-dependent.

Did you apply any resampling or time-alignment between PPG and IMU signals?

5. Ambiguity in "IMU" Definition

Please clearly define what you mean by “IMU” in the context of your device:

Are you using accelerometer only, gyroscope only, or both?

If both are present, are they all used in the signal fusion?

6. Cross-Validation and Subject Separation

You mention using Leave-One-Subject-Out (LOSO) cross-validation. Please confirm:

Was this strict LOSO, with no subject data leakage during feature extraction or normalization?

Was LOSO also applied to the deep learning model, or just traditional classifiers?

7. PPG-DaLiA Evaluation and Ground Truth

You evaluate your model on the PPG-DaLiA dataset, which does not contain ground truth for pulse loss or smartwatch idle status.

How did you define the labels for this dataset?

How did you differentiate normal vs. pulse loss vs. non-usage in the absence of ground truth?

Please explain how Doppler Ultrasound, used as ground truth in your dataset, relates to the evaluation on PPG-DaLiA, where no such ground truth is available.

8. Comparison with Existing Methods

The manuscript does not provide any benchmark comparison with previous methods in pulse detection or loss-of-pulse detection.

Please compare your model with at least one existing baseline or state-of-the-art method to contextualize the reported accuracy.

Reviewer #2: The paper presents a system based on smartwatches with the aim to detect the loss of pulse. The paper is well writen and structured although some improvements can be achieved:

- The smartwatch (Samsung Gear S3 Frontier) characteristics should be listed as well as the characteristics of the smartwatch sensors (vendor, resolution, maximum range...)

- The sentence "An example setup of the data collection is shown in Figure 1" is writen twice in page 4

- The reference to Figure 3 in page 5 is not clear. I am not sure if it is really to Figure 3 or Figure 2. Check it. Consequently, Figure 2 or 3 are not referenced or explained in the text as only one is referenced.

- The paper compares the performance of some models. However they are not explained in detail. That is, the parameters of each model are not presented. For instance, what is the architecture of the employed Neural Network Model? The obtained performance using a NN is very dependant of its architecture.

- Table 4 (in page 11) should be placed after (or closer) to its reference (page 13).

- The sentence in page 15 "Second, when the subjects wore ..." seems to be incomplete.

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Reviewer #1: Yes: Kianoosh Kazemi

Reviewer #2: Yes: Francisco J. González-Cañete

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PONE-D-25-29278R1Smartwatch-Based Detection of Loss of PulsePLOS ONE

Dear Dr. Demirel,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 07 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Diaa Ahmed Mohamed Ahmedien, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Dear authors,

Thank you for your careful revision, it would be helpful to further consider the first revierwer's comments as a final revision.

Best regards

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I would encourage the authors to discuss and compare their approach with other recent work on smartwatch-based loss of pulse detection. For instance, Shah et al. (NShah, K., Wang, A., Chen, Y. et al. Automated loss of pulse detection on a consumer smartwatch. Nature 642, 174–181 (2025). https://doi.org/10.1038/s41586-025-08810-9) presented an automated loss of pulse detection system implemented on a consumer smartwatch, using a multi-stage pipeline with PPG, motion data, and a lightweight convolutional neural network trained on 528 engineered features.

Given that your work also focuses on smartwatch-based pulse loss detection with machine learning, it would strengthen the manuscript to position your framework in relation to this paper, highlighting methodological similarities (e.g., multimodal PPG + motion sensing, simulation of pulse loss via occlusion) as well as differences (e.g., dataset openness, model architectures, evaluation settings).

Reviewer #2: The requirements of the reviewers seem to be accomplished, at least those made by me in the first round of review.

For future responses to reviewers I suggest to include the full text of the reviewer, instead of a short sentence, in order to be understandable by the rest of reviewers or even to be remembered by the reviewer that is doing the second round of reviews. That way, the reviewers know exactly what was requested in the first round of reviews.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Kianoosh Kazemi

Reviewer #2: No

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NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications.

Smartwatch-Based Detection of Loss of Pulse

PONE-D-25-29278R2

Dear Dr. Demirel,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Agnese Sbrollini

Academic Editor

PLOS One

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript is written scientifically. The authors has addressed all the comments. and the discussion is now fair with comparing their method with other existing methods.

Reviewer #2: The requirements of the reviewers seem to be accomplished. Hence, it can be accepted as is without further modificaciones.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: KIANOOSH KAZEMI

Reviewer #2: Yes: Francisco Javier González Cañete

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