Consumer Smartwatch Technology in Health and Performance Research: Validity, Limitations, and Real-World Applications

Round 1

Reviewer 1 Report

The manuscript provides a well-written and valuable overview of smartwatch technology in health and performance research. I do not see any major problems with the work, but I believe the analysis would strongly benefit from more specific details to increase its practical value for researchers.

To improve the manuscript, please address the following points:

1. Literature search methodology: the manuscript currently transitions directly into the review without explaining how the literature was sourced. Please add a brief paragraph outlining your search strategy (e.g., databases used, keywords, inclusion/exclusion criteria).

2. Different devices: the current analysis treats "smartwatches" as a broad category. Please provide more detail on specific devices currently available, differentiating between high-end sport/medical watches and budget-tier fitness trackers. Discussing their respective strengths and weaknesses would make the paper much more robust and interesting.

3. Demographic biases: while you correctly identify skin tone as a confounder for PPG sensors, the discussion on algorithmic bias should be slightly expanded. Please briefly address how algorithms perform across other critical demographic variables, such as varying age brackets, body mass indexes, or biological sexes.

4. Table 1 refinements: table 1 is a good conceptual summary, but stating that validity is "acceptable" or "variable" provides limited practical value. Please update the table to include more specific, peer-reviewed quantitative error ranges where available, and ideally note distinctions between different tiers or models of smartwatches.

Author Response

Reviewer 1 Original Comments
The manuscript provides a well-written and valuable overview of smartwatch technology in health and performance research. I do not see any major problems with the work, but I believe the analysis would strongly benefit from more specific details to increase its practical value for researchers.

We would first and foremost like to thank the reviewer for taking the time to review this manuscript. Your thoughtful review has led us to make necessary improvements to the manuscript. We acknowledge the time and commitment you have invested in reviewing this article and appreciate your input. We believe that we have addressed your concerns, as well as those from the other reviewers, with the revised draft and are confident that the comments and subsequent changes made to the manuscript will improve the quality and readability of the paper. Please find our responses to your comments below, where we have left your comments in regular font and provided a brief explanation of our edits in red font. In the paper, we have highlighted any changes in yellow for your convenience.

To improve the manuscript, please address the following points:

1. Literature search methodology: the manuscript currently transitions directly into the review without explaining how the literature was sourced. Please add a brief paragraph outlining your search strategy (e.g., databases used, keywords, inclusion/exclusion criteria).
   Thank you for this helpful feedback. We have revised the manuscript to address this concern by including a new approach section (section 1.1, lines 96-111) that clarifies the purpose and scope of the narrative review, and the databases and search approach used to identify relevant literature.
2. Different devices: the current analysis treats "smartwatches" as a broad category. Please provide more detail on specific devices currently available, differentiating between high-end sport/medical watches and budget-tier fitness trackers. Discussing their respective strengths and weaknesses would make the paper much more robust and interesting.
   Thank you for this suggestion. We revised the manuscript to better differentiate among major categories of consumer wrist-worn devices. Specifically, we added a new subsection (section 3.1, lines 245-274) describing the differences between wrist-worn activity/fitness trackers, general-purpose smartwatches, and premium performance-focused sport watches. We specifically avoided using any brand names or models and instead kept the discussion more general. We also added language emphasizing that device tier should not be treated as a surrogate for validity and that device selection should instead be guided by the specific metric, population, activity, environment, and decision of interest, which is in line with the overall framework provided in the manuscript.
3. Demographic biases: while you correctly identify skin tone as a confounder for PPG sensors, the discussion on algorithmic bias should be slightly expanded. Please briefly address how algorithms perform across other critical demographic variables, such as varying age brackets, body mass indexes, or biological sexes.
   We want to thank the reviewer for this important suggestion. We expanded the discussion of demographic and algorithmic bias beyond skin tone by adding text addressing age, body mass index, wrist circumference, adiposity, and biological sex (lines 336-347). The revision explains how these characteristics may affect sensor-signal quality, device fit, physiological model assumptions, and derived heart rate.
4. Table 1 refinements: table 1 is a good conceptual summary, but stating that validity is "acceptable" or "variable" provides limited practical value. Please update the table to include more specific, peer-reviewed quantitative error ranges where available, and ideally note distinctions between different tiers or models of smartwatches.
   We have revised Table 1 to replace broad descriptors such as “acceptable” or “variable” with more specific quantitative error ranges where available from the peer-reviewed literature summarized in the Section 4 text. We also added clarification in the Table caption to caution the reader that performance may differ by device model, firmware, population, activity, environment, and criterion reference.

Reviewer 2 Report

This review delivers a well-structured, practical framework for assessing consumer smartwatch-derived metrics across health, rehabilitation, and performance research contexts. By distinguishing raw sensor signals from higher-level algorithmic outputs and systematically reviewing validity evidence for both established and emerging metrics, it provides much-needed guidance for researchers and practitioners working with wearable data. I recommend acceptance of the manuscript subject to a minor revision addressing the following points. There are several typographical errors in the labels of Figure 1, including misspellings such as accelertion, MOpical waveorm and Casifcindig, which detract from the clarity of the conceptual framework. The authors should carefully proofread and correct all figure labeling errors. Minor redundant phrasing and grammatical inconsistencies are present in the main text, such as the duplicated “Because VO₂” expression in Section 4.2. A careful line-by-line edit would further refine the manuscript’s fluency and textual precision. Research on multi-frequency smartphone positioning performance evaluation insights into a-gnss ppp-b2b services and beyond provides valuable technical context for smartwatch outdoor spatiotemporal metrics. The authors may enrich the literature review section with a short discussion of such advanced terminal positioning technologies and their implications for wearable measurement accuracy. The authors are encouraged to expand the conclusion section with a more detailed discussion of the core technical limitations of current smartwatch sensing technology, as well as under-explored potential application scenarios for future research and practice. Work on a wrist-worn multimodal system for seamless pedestrian navigation and continuous health monitoring sensor fusion in the wild demonstrates the value of advanced multimodal sensor fusion. The authors could add a brief discussion on how enhanced multi-source fusion could improve the robustness and ecological validity of the proposed smartwatch measurement framework. These revisions will improve the paper’s clarity and ensure that it is of the highest quality for publication. I look forward to seeing the revised version.

Author Response

Reviewer 2 Original Comments

This review delivers a well-structured, practical framework for assessing consumer smartwatch-derived metrics across health, rehabilitation, and performance research contexts. By distinguishing raw sensor signals from higher-level algorithmic outputs and systematically reviewing validity evidence for both established and emerging metrics, it provides much-needed guidance for researchers and practitioners working with wearable data. I recommend acceptance of the manuscript subject to a minor revision addressing the following points.

We would first and foremost like to thank the reviewer for taking the time to review this manuscript. Your thoughtful review has led us to make necessary improvements to the manuscript. We acknowledge the time and commitment you have invested in reviewing this article and appreciate your input. We believe that we have addressed your concerns, as well as those from the other reviewers, with the revised draft and are confident that the comments and subsequent changes made to the manuscript will improve the quality and readability of the paper. Please find our responses to your comments below, where we have left your comments in regular font and provided a brief explanation of our edits in red font. In the paper, we have highlighted any changes in yellow for your convenience.

There are several typographical errors in the labels of Figure 1, including misspellings such as accelertion, MOpical waveorm and Casifcindig, which detract from the clarity of the conceptual framework. The authors should carefully proofread and correct all figure labeling errors.

Thank you for identifying this issue. We carefully reviewed all labels in Figure 1 and confirmed the intended wording, including “Raw acceleration,” “Optical waveform,” and “Classification/modeling.” Although the labels appeared correct in the original figure file from our end, we suspect that image compression or rendering during manuscript conversion may have reduced their clarity. We have therefore re-exported Figure 1 at higher resolution, replaced the figure in the revised manuscript, and carefully proofread all labels to ensure readability and consistency.

Minor redundant phrasing and grammatical inconsistencies are present in the main text, such as the duplicated “Because VO₂” expression in Section 4.2. A careful line-by-line edit would further refine the manuscript’s fluency and textual precision.

Thank you for this helpful comment. We conducted a careful line-by-line review of the manuscript and corrected grammatical inconsistencies, redundant phrasing, and punctuation errors. We also revised the concluding sentences of Section 4.2 to remove repetition related to VO₂max and energy expenditure as the reviewer mentioned, and consolidated the discussion of shared sources of error. Additional minor copyediting was performed throughout the manuscript to improve clarity, precision, fluency, and consistency.

Research on multi-frequency smartphone positioning performance evaluation insights into a-gnss ppp-b2b services and beyond provides valuable technical context for smartwatch outdoor spatiotemporal metrics. The authors may enrich the literature review section with a short discussion of such advanced terminal positioning technologies and their implications for wearable measurement accuracy.

Thank you for this suggestion. We added a brief discussion in Section 4.5 (lines 519-529) describing emerging multi-frequency and multi-constellation GNSS approaches. We also clarified that current evidence is primarily derived from advanced smartphone terminals, but that these technologies may inform future improvements in smartwatch-derived distance, pace, route, and elevation estimates.

The authors are encouraged to expand the conclusion section with a more detailed discussion of the core technical limitations of current smartwatch sensing technology, as well as under-explored potential application scenarios for future research and practice.

Thank you for this suggestion. We expanded the last paragraph of the Conclusion (lines 796-807) to address this comment. We have added contextual limitations and several under-explored future applications, including context-aware rehabilitation monitoring, identification of deviations from individual baselines, integration of health and location data, and monitoring across real-world environmental transitions.

Work on a wrist-worn multimodal system for seamless pedestrian navigation and continuous health monitoring sensor fusion in the wild demonstrates the value of advanced multimodal sensor fusion. The authors could add a brief discussion on how enhanced multi-source fusion could improve the robustness and ecological validity of the proposed smartwatch measurement framework.

Thank you for this recommendation. We expanded the discussion of multisensor integration in Section 3 (lines 277-287) to describe how future systems may combine physiological, inertial, positional, and environmental signals while dynamically accounting for signal quality. We also added recent work demonstrating the feasibility of integrated wrist-worn health monitoring and pedestrian navigation, while noting the need for independent real-world validation.

These revisions will improve the paper’s clarity and ensure that it is of the highest quality for publication. I look forward to seeing the revised version.