Detection and analysis of pulse waves during sleep via wrist-worn actigraphy

Johannes Zschocke; Maria Kluge; Luise Pelikan; Antonia Graf; Martin Glos; Alexander Müller; Rafael Mikolajczyk; Ronny P. Bartsch; Thomas Penzel; Jan W. Kantelhardt

doi:10.1371/journal.pone.0226843

Peer Review History

Original SubmissionJuly 24, 2019
6 Nov 2019 Decision Letter - Tomohiko Ai, Editor PONE-D-19-20716 Detection and analysis of pulse waves during sleep via wrist-worn actigraphy PLOS ONE Dear Priv.-Doz. Dr. Kantelhardt, 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. Your paper was reviewed by an expert in the field and myself. Although the reviewer's response is somehow positive, there are several points to be clarified. Also, figure legends and discussion need be modified. Please read the comments carefully, and address the issues accordingly. We would appreciate receiving your revised manuscript by Dec 21 2019 11:59PM. 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The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide. [Note: HTML markup is below. Please do not edit.] 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 ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 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: Yes ****** 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 ****** 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: The authors demonstrate the utility of wrist accelerometers to identify heartbeats and to extract heart beat variability. The technical aspects of work are solid, and provided in sufficient detail. The findings are clearly stated, and the manuscript is well-written. The study presents a novel approach to dissect physiological information from wrist activity during sleep and I recommend publication. There are several important points that the authors should address in the revised manuscript before publication: 1. Since the age of subjects varies from 18 to 80 years old, having in mind that HRV is reduce in the elderly subjects, do the results depend on the age of the subjects? 2. Many figures (Figs. 1,2,4,5,10) in the manuscript are lack of legends, which creates difficulty for reader to understand the figure. The authors should add legends for these figures. 3. As authors showed in Fig. 5, the x axis (part (a)) yields the most consistent PWP positions with respect to the R peaks in the ECG. Is it always true that in a specific direction (x) that PWP positions are consistent with R peaks, or in the different subjects such consistency changes in different directions? 2. it appears that the authors are not familiar with pioneer studies that utilize wrist actigraphy dynamics. First investigation that demonstrated physiological relevance in the distribution and correlations of wrist activity fluctuations independent of level of physical activity was published in 2003 � Hu K, et. al. Novel multiscale regulation in human motor activity. In "Fluctuations and Noise in Biological, Biophysical, and Biomedical Systems", edited by Bezrukov SM, Frauenfelder H, Moss F. SPIE Proceedings 5110, 2003; p. 235-243. � Hu K, et. al. Non-random fluctuations and multi-scale dynamics regulation of human activity. Physica A 2004;337(1-2):307-318. It was later demonstrated that wrist activity fluctuations are also related to circadian rhythms and to the role of the SCM area in the brain � Ivanov PCh, et. al. Endogenous circadian rhythm in human motor activity uncoupled from circadian influences on cardiac dynamics. Proc. Natl. Acad. Sci. 2007; 104(52):20702-20707. � Hu K, et. al. The suprachiasmatic nucleus functions beyond circadian rhythm generation. Neuroscience 2007; 149(3):508-517. The authors should give credit to these earlier works. 3. In the context of pause wave interval (PWI) dynamics, the authors should relate their results to a pioneering study in 2002, which utilized PWI to investigate HRV during exercise with the need of ECG electrons: � Karasik R, et. al. Correlation differences in heartbeat fluctuations during rest and exercise. Physical Review E, 2002; 66(6): 062902(4). 4. The authors utilize analytic signal approach in Hilbert transform to extract the amplitude of wrist acceleration signals, and to identify peaks in actigraphy dynamics that correspond to individual heartbeat. The authors should be informed that one of the first publications with Hilbert transform in physiological dynamics was used to detect the amplitude of heart rate variability fluctuations: � Ivanov PCh, et. al. Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis. Nature 1996; 383: 323–327. � Ivanov PCh, et. al. Scaling and universality in heart rate variability distributions. Physica A 1998; 249: 587–593. ****** 6. 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: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0226843.r001
Revision 1
22 Nov 2019 Author Response (Please see the resubmission letter, where this text is better formated.) Point-by-point response to the reviewer We thank the reviewer for his/her careful evaluation and additional comments. Below we outline our point-by-point response to his/her concerns. 1. Comment: Since the age of subjects varies from 18 to 80 years old, having in mind that HRV is reduced in the elderly subjects, do the results depend on the age of the subjects? Response: We thank the reviewer for raising this important point. We have divided our database into three age groups of similar sizes, see the new Table 3. As shown by the revised histograms in Fig. 7, the revised Bland-Altman plots (Fig. 8), and Table 3, our algorithm’s performance does not depend on the age of the subjects. We have added one paragraph on page 11 (lines 254-262) to present these findings: These percentages hardly depend on the age of the subjects. No systematic differences between three age groups of approximately equal size (see Table 3) can be observed when comparing the corresponding histograms for each color in Fig 7. This indicates that the reconstruction of pulse waves from wrist actigraphy as presented in this paper does not depend on age. Furthermore, the results in Table 3 show that there is no systematic age dependence in the PWI algorithm selection of particular orientation axes. Across all age groups, the y axis acceleration data is selected most frequently for the PWI detection, followed by the z axis data. The x axis, pointing towards the hand, is only quite rarely selected. However, we clearly see the reduction with age in HRV as quantified by SDNN and RMSSD. Interestingly, from the RR interval analysis we obtain very similar values of SDNN and RMSSD for the age groups as have been found in Schmitt et al. IEEE 2009;56(5):1564-1573 (reference [35] in the paper). To better explain this point, we have modified the caption of Fig. 8 and added the following text on page 12 (lines 291-299): The colored symbols in Fig 8, corresponding to the results of the three age groups (see Table 3), show no systematic dependence on age, supporting the conclusion from Fig 7 that our reconstruction of PWI from wrist actigraphy does not depend on age. Furthermore, the mean SDNN and RMSSD values listed in Table 3 for each of the three groups show that the reduction of SDNN and RMSSD with age reported by Schmitt et al. [35] similarly occurs for the HRV parameters derived from RRI and PWI, although their absolute values are different. Apparently, the decrease occurs before the age of approximately 40-50 years, since our results for the last two age groups (46-56 and 57-80 years, respectively) are practically identical. We have also revised Fig. 9 to show the age dependence of pulse transit times and added the following text on page 13 (lines 317-320): However, PTT values in young subjects seem to be a bit longer than those in the elderly, since a slight difference between the young group and the other two groups can be seen in Fig 9(a) and leads to significantly different means as reported in Table 3. 2. Comment: Many figures (Figs. 1,2,4,5,10) in the manuscript are lack of legends, which creates difficulty for reader to understand the figure. The authors should add legends for these figures. Response: We agree with the reviewer and have added the legends accordingly. 3. Comment: As authors showed in Fig. 5, the x axis (part (a)) yields the most consistent PWP positions with respect to the R peaks in the ECG. Is it always true that in a specific direction (x) that PWP positions are consistent with R peaks, or in the different subjects such consistency changes in different directions? Response: We have addressed this important point in our new Table 3, where the fractions of pulse wave peaks derived from the data of each acceleration axis are reported for all three age groups. The results show that PWP from the x axis are in fact least frequent; more than half of the consistent peaks come from the y axis. We have added the following two sentences (lines 258-262). Furthermore, the results in Table 3 show that there is no systematic age dependence in the PWI algorithm selection of particular orientation axes. Across all age groups, the y axis acceleration data is selected most frequently for the PWI detection, followed by the z axis data. The x axis, pointing towards the hand, is only quite rarely selected. 4. Comment: It appears that the authors are not familiar with pioneer studies that utilize wrist actigraphy dynamics. First investigation that demonstrated physiological relevance in the distribution and correlations of wrist activity fluctuations independent of level of physical activity was published in 2003: Hu K, et. al. Novel multiscale regulation in human motor activity. In "Fluctuations and Noise in Biological, Biophysical, and Biomedical Systems", edited by Bezrukov SM, Frauenfelder H, Moss F. SPIE Proceedings 5110, 2003; p. 235-243; Hu K, et. al. Non-random fluctuations and multi-scale dynamics regulation of human activity. Physica A 2004;337(1- 2):307-318. It was later demonstrated that wrist activity fluctuations are also related to circadian rhythms and to the role of the SCM area in the brain: Ivanov PCh, et. al. Endogenous circadian rhythm in human motor activity uncoupled from circadian influences on cardiac dynamics. Proc. Natl. Acad. Sci. 2007; 104(52):20702-20707. Hu K, et. al. The suprachiasmatic nucleus functions beyond circadian rhythm generation. Neuroscience 2007; 149(3):508-517. The authors should give credit to these earlier works. Response: We thank the reviewer for pointing this out. We have now added these references accordingly on pages 2 and 3 in the revised manuscript. The new text reads: First investigations that demonstrated physiological relevance in the distribution and autocorrelations of wrist activity fluctuations independent of level of physical activity were published by Hu et al. [13,14]. In later studies it has been shown that wrist activity fluctuations are also related to the circadian rhythm and to the role of the suprachiasmatic nucleus in the brain [15,16] that is responsible for regulating many different body functions on a 24-hour cycle. 5. Comment: In the context of pause wave interval (PWI) dynamics, the authors should relate their results to a pioneering study in 2002, which utilized PWI to investigate HRV during exercise with the need of ECG electrodes: Karasik R, et. al. Correlation differences in heartbeat fluctuations during rest and exercise. Physical Review E, 2002; 66(6): 062902(4). Response: We thank the reviewer for pointing this out. We have added this reference on page 4 in the revised manuscript together with the following text: We refer to [22] for an early application of using pulse wave intervals from plethysmography to study cardiac dynamics and investigate HRV during rest and exercise without ECG electrodes. 6. Comment: The authors utilize analytic signal approach in Hilbert transform to extract the amplitude of wrist acceleration signals, and to identify peaks in actigraphy dynamics that correspond to individual heartbeat. The authors should be informed that one of the first publications with Hilbert transform in physiological dynamics was used to detect the amplitude of heart rate variability fluctuations: Ivanov PCh, et. al. Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis. Nature 1996; 383: 323–327; Ivanov PCh, et. al. Scaling and universality in heart rate variability distributions. Physica A 1998; 249: 587–593. Response: We thank the reviewer for pointing this out. These references are now added on page 8 with the following text: Among the first applications of this approach to physiological dynamics are the works of Ivanov et al. who used Hilbert transform to detect the amplitude of heart rate variability fluctuations [32,33]. https://doi.org/10.1371/journal.pone.0226843.r002
9 Dec 2019 Decision Letter - Tomohiko Ai, Editor Detection and analysis of pulse waves during sleep via wrist-worn actigraphy PONE-D-19-20716R1 Dear Dr. Kantelhardt, We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements. Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication. Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. With kind regards, Tomohiko Ai, M.D., Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0226843.r003
Formally Accepted
18 Dec 2019 Acceptance Letter - Tomohiko Ai, Editor PONE-D-19-20716R1 Detection and analysis of pulse waves during sleep via wrist-worn actigraphy Dear Dr. Kantelhardt: I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. For any other questions or concerns, please email plosone@plos.org. Thank you for submitting your work to PLOS ONE. With kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Tomohiko Ai Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0226843.r004

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