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Article
Peer-Review Record

Influence of Chinstrap Stiffness on Cerebrospinal Fluid Dynamics and Brain Stress in Helmet Impacts

Appl. Sci. 2025, 15(10), 5459; https://doi.org/10.3390/app15105459
by Jonathan Mayer 1, Daniel Nasef 1, Molly Bekbolatova 1, Hallie Zwibel 2 and Milan Toma 1,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Appl. Sci. 2025, 15(10), 5459; https://doi.org/10.3390/app15105459
Submission received: 11 April 2025 / Revised: 7 May 2025 / Accepted: 12 May 2025 / Published: 13 May 2025
(This article belongs to the Special Issue Advances in Fluid Mechanics Analysis)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Review Feedback on the Manuscript
"Influence of Chinstrap Stiffness on Cerebrospinal Fluid Dynamics and Brain Stress in Helmet Impacts"

Scientific Rigor, Novelty, and Structure

The study demonstrates strong scientific rigor by employing advanced computational methods—including SPH, FSI, and GPU-accelerated simulations—to address a clinically relevant problem in sports medicine. The integration of detailed neuroanatomical structures with helmet components is particularly commendable, and material properties (e.g., viscoelastic brain tissue, CSF bulk modulus) are well-supported by prior literature. A key novelty lies in its focus on chinstrap stiffness, an understudied aspect of helmet design, where identifying a hazardous intermediate stiffness regime challenges conventional safety paradigms.

The findings hold significant translational potential, offering actionable insights for helmet manufacturers by highlighting the need to balance elasticity and rigidity in chinstrap design. The nonlinear stiffness-stress relationship directly impacts safety standards (e.g., ASTM F1446), particularly in defining risk thresholds for concussion mitigation. Structurally, the manuscript is well-organized, with clear figures and tables supporting its conclusions. The computational framework is robust, utilizing high-resolution modeling (~94,000 SPH particles, ~156,000 tetrahedral elements), and the technical writing is precise, with minimal grammatical errors.

Weaknesses & Revisions Needed

While the study demonstrates strong computational methodology, several limitations should be addressed to strengthen its impact. A major gap is the reliance on simulations without experimental validation using physical helmet tests, such as cadaveric studies or sensor-equipped dummy impacts. Although the model references prior cadaveric data, incorporating helmet-specific validation would significantly bolster the findings. Additionally, the study would benefit from systematic comparisons with existing research on chinstrap performance in football or military helmets, such as Singleton (2017) or Bustamante et al. (2019), to better contextualize its contributions. The model's simplified assumptions—excluding skin, meninges, and rotational forces—may limit real-world applicability. Expanding the limitations section to discuss how these omissions could influence results (e.g., energy absorption by soft tissues, rotational shear effects) would improve transparency. Furthermore, focusing solely on linear impacts overlooks the critical role of rotational accelerations in concussions, which should be explicitly emphasized in the Discussion and Conclusion. In terms of presentation, some sections are redundant (e.g., repeated discussions of intermediate stiffness risks), and minor grammatical errors require proofreading. Enhancing Figure 11 with quantitative annotations (e.g., energy absorption percentages) and condensing Table 1’s outlier analysis in the main text would improve clarity.

For acceptance, the following revisions are essential:

  • Addressing validation gaps through proposed experimental follow-ups or comparative literature
  • Expanding comparative analysis with prior helmet studies. Add a paragraph comparing findings to studies like Singleton (2017) on motorcycle helmets or Bustamante et al. (2019) on football helmets, highlighting how this study advances the field.
  • Clarifying limitations regarding anatomical simplifications and rotational dynamics. Emphasize this limitation in the Discussion and Conclusion. Expand the limitations section to discuss how these exclusions might bias results (e.g., energy absorption by skin/meninges, shear stress from rotational forces).
  • Enhancing translational impact with actionable design guidelines for industry standards (e.g., NOCSAE, MLB). These refinements would solidify the study’s rigor and applicability. Explicitly address this limitation and propose future work involving sensor-equipped helmets or dummy head testing.
  • Condense for conciseness to avoid repetitive discussions (e.g., risks of intermediate stiffness in Results and Discussion)
  • Figure 11’s schematic could be enhanced with quantitative annotations (e.g., % energy absorbed).
  • Table 1’s outlier analysis could be summarized more succinctly in the main text.
  • Add a figure by combining 3 (b), 4 (b), 5 (b), 6 (b), and 7 (b), and add a different color line to differentiate curves.

Author Response

We sincerely thank the reviewer for their careful reading and thoughtful feedback. Your insightful comments and suggestions have helped us strengthen the manuscript substantially, both in scientific rigor and clarity (the edited/added parts of the manuscript are highlighted in red color). We greatly appreciate the time and expertise you have devoted to improving this work.

Comment 1: Addressing validation gaps through proposed experimental follow-ups or comparative literature. Expanding comparative analysis with prior helmet studies. Add a paragraph comparing findings to studies like Singleton (2017) on motorcycle helmets or Bustamante et al. (2019) on football helmets, highlighting how this study advances the field.

Response 1: We’ve now included a completely new subsection to discuss our results in comparison with those mentioned in your comment and others. Our reference list has substantially increased.

 

Comment 2: Clarifying limitations regarding anatomical simplifications and rotational dynamics. Emphasize this limitation in the Discussion and Conclusion. Expand the limitations section to discuss how these exclusions might bias results (e.g., energy absorption by skin/meninges, shear stress from rotational forces).

Response 2: To address your comment, we’ve modified the text in three sections: Methods, Discussion, Conclusion.

 

Comment 3: Enhancing translational impact with actionable design guidelines for industry standards (e.g., NOCSAE, MLB). These refinements would solidify the study’s rigor and applicability. Explicitly address this limitation and propose future work involving sensor-equipped helmets or dummy head testing.

Response 3: Thank you for bringing that up. We’ve added a completely new subsection to the discussion section to address this point.

 

Comment 4: Figure 11’s schematic could be enhanced with quantitative annotations (e.g., % energy absorbed).

Response 4: Thank you for encouraging us to make the figure easier for the readers to interpret. We’ve implemented your excellent idea!

 

Comment 5: Table 1’s outlier analysis could be summarized more succinctly in the main text.

Response 5: We revised the sections discussing Table 1 to ensure that the analysis is presented more succinctly, focusing on the key insights without excessive detail. We recognize that preferences for the depth of analysis can vary among readers; some favor concise summaries that capture essential findings, while others prefer more detailed discussions that reiterate key points multiple times for clarity. In this manuscript, we have aimed to strike a balance between these two approaches, providing a comprehensive overview while maintaining brevity. However, we understand the importance of clarity and efficiency in scientific communication.

 

Comment 6: Add a figure by combining 3 (b), 4 (b), 5 (b), 6 (b), and 7 (b), and add a different color line to differentiate curves.

Response 6: Another excellent idea! As requested, the combination of the above figures is now shown in new Figure 9 of the revised article.

 

Comment 7: Condense for conciseness to avoid repetitive discussions (e.g., risks of intermediate stiffness in Results and Discussion)

Response 7: We appreciate the reviewer’s suggestion to condense repetitive discussions, particularly regarding the risks associated with intermediate stiffness. Our intent in reiterating key findings in both the Results and Discussion was to maximize accessibility for a broad readership. Many readers focus on specific sections (such as the Abstract, Results, Figures, or Discussion) rather than reading the full text. Repeating critical interpretations ensures that the major conclusions are accessible regardless of reading path. This approach is common, where clarity and transfer of key insights take precedence, and is consistent with our writing style. We respectfully request that the repetition be retained to facilitate reader comprehension, unless the editorial team deems this inconsistent with journal policy.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

manuscript no. applsci-3611141 entitled "Influence of Chinstrap Stiffness on Cerebrospinal Fluid Dynamics and Brain Stress in Helmet Impacts" is very interesting and well organized. 

My questions mostly result from my interest and curiosity in the topic presented and not from the need to correct its content.

 The authors write that: … the risk of injury especially incereases when the pitch velocity is over 75 miles per hour… – what value of impact energy is equal to this speed?

Why was the velocity of 40 m/s (~89.5 miles per hour) used in the simulations and not, for example, 70 or 75 miles/per hour?

How many people (on average, estimated value) constitute 1.3% of the most common injuries? Are there any standards or studies in the US that allow us to estimate the quality of a baseball helmet?  

Are there any literature reports that allow us to verify whether the simulations performed are consistent with the real results (are they very similar to the results of studies performed in real conditions)? 

What do the authors think:

a)  Would the same or similar results be obtained if the helmet had shock-absorbing pads made of a substance e.g. dilatant fluid with non-Newtonian properties such as D3O? Would this affect the results obtained?

b)  Could this type of simulation (presented in article) be applied (after appropriate modification, e.g. in terms of impact velocity, etc.) to other types of products, e.g. motorcycle helmets or ballistic helmets?

c)  Would a different chainstrap system, i.e. a different arrangement or positioning of the harness and/or straps, have an impact on the obtained results?

It would be good to add more literature from 2025-2023 to references.

Best regards,

Reviewer

Author Response

Comment 1: My questions mostly result from my interest and curiosity in the topic presented and not from the need to correct its content.

Reply 1: Thank you very much for your thoughtful, constructive, and collegial review. We greatly appreciate your engagement with our work, your insightful questions, and your attention to detail. Your comments not only helped us improve the accuracy and clarity of our manuscript, but also prompted us to reflect more deeply on the methodology and broader implications of our study. We are grateful for your curiosity and the spirit of scientific dialogue you brought to the review process.

Comment 2: The authors write that: … the risk of injury especially increases when the pitch velocity is over 75 miles per hour… – what value of impact energy is equal to this speed?

Reply 2: I admit that, as the faculty supervisor, I should have checked the statistics included in the introduction by the students. Apparently, the cited reference supporting that statement does not mention the figure of 75 mph. However, I found another source that calculated this value at 86.2 mph. Therefore, following the standard kinetic energy formula, the impact energy of a baseball thrown at 86.2 mph is about 108 joules. I have now rewritten the paragraph to ensure that all statistics are factually accurate and that the citations genuinely support the statements made. This experience highlights the importance for faculty members to critically assess information, especially when it may have been obtained through AI-powered search engines. We are still learning to recognize such issues, and it will take some time for us to fully adapt to the new AI-driven world.

Comment 3: Why was the velocity of 40 m/s (~89.5 miles per hour) used in the simulations and not, for example, 70 or 75 miles/per hour?

Reply 3: By selecting a velocity above the 86.2 mph injury threshold, the study ensures that the helmet and chinstrap system are evaluated under severe, yet plausible, impact conditions. In Major League Baseball, fastballs frequently reach or exceed 90 mph. Using 40 m/s (89.5 mph) aligns the simulation with the velocities that batters are most likely to encounter at the highest levels of play. Additionally, simulating impacts at a higher velocity than the minimum injury threshold (86.2 mph) provides a safety margin. If a helmet and chinstrap system can effectively mitigate stress and injury risk at 40 m/s, it will also be effective at lower velocities.

Comment 4: How many people (on average, estimated value) constitute 1.3% of the most common injuries? Are there any standards or studies in the US that allow us to estimate the quality of a baseball helmet?  

Reply 4: Upon reviewing the introduction, I found that the statistic of 1.3% cited in the first paragraph was not actually supported by the referenced source, again. I have now fully reviewed everything, replacing the unsupported statistics with accurate, up-to-date data and ensuring that all statements are properly referenced with appropriate citations. I am grateful for your question, as it prompted me to double-check the statistics and correct these inconsistencies.

Comment 5: Are there any literature reports that allow us to verify whether the simulations performed are consistent with the real results (are they very similar to the results of studies performed in real conditions)? 

Reply 5: Thank you for your question regarding the consistency of our simulation results with real-world outcomes. In response, we have added a new section to the revised manuscript (see Section 4.1, “Comparison with Prior Helmet Studies”) that specifically addresses this issue. In this section, we discuss relevant literature on helmet impact biomechanics and compare our simulation findings with published experimental and epidemiological studies in both football and motorcycle helmet research. We also highlight how our computational model was validated against prior studies, including those using cadaveric data, to enhance the credibility of our results. We appreciate your suggestion, which prompted us to clarify and expand on the relationship between our simulations and real-world data.

Comment 6: a)  Would the same or similar results be obtained if the helmet had shock-absorbing pads made of a substance e.g. dilatant fluid with non-Newtonian properties such as D3O? Would this affect the results obtained?

Reply 6: If the helmet’s padding were replaced or supplemented with a non-Newtonian, shear-thickening material like D3O, the results would likely differ in important ways. So, Yes, the use of a non-Newtonian, shear-thickening liner would likely reduce the absolute magnitude of intracranial stresses observed in all chinstrap configurations. However, the relative trends identified in our study, namely, the nonlinear relationship between chinstrap stiffness and brain stress, and the existence of a hazardous intermediate stiffness regime, would likely persist, since these are governed by the mechanics of force transmission and helmet stability, not just by the liner’s properties. Future work could extend our computational framework to explicitly model non-Newtonian liner materials and quantify their combined effects with chinstrap stiffness on brain injury risk.

Comment 7: b)  Could this type of simulation (presented in article) be applied (after appropriate modification, e.g. in terms of impact velocity, etc.) to other types of products, e.g. motorcycle helmets or ballistic helmets?

Reply 7: Yes, with appropriate modifications to reflect the specific helmet design, materials, and impact scenarios, the simulation methodology described in our article can be extended to analyze the protective performance of motorcycle, ballistic, or other helmet types. Numerous studies have successfully applied FEA and related computational methods to motorcycle and ballistic helmets, demonstrating the feasibility of such adaptations.

Comment 8: c)  Would a different chinstrap system, i.e. a different arrangement or positioning of the harness and/or straps, have an impact on the obtained results?

Reply 8: Yes, the arrangement and positioning of the chinstrap system, including alternative harness geometries or strap anchoring points, could indeed influence the way forces are transmitted during impact, potentially affecting both helmet stability and the distribution of stress within the brain and skull. A direct comparison between different chinstrap arrangements or harness positions would require a separate, dedicated study in which those variables are systematically varied and compared side-by-side. Such work would be a valuable extension of our current findings and could be explored in future research using the same computational framework.

Comment 9: It would be good to add more literature from 2025-2023 to references.

Reply 9: We have now substantially increased the number of references, especially those published recently. Thank you for pointing that out.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors' responses to the reviewers' feedback on the initial manuscript are satisfactory, and the manuscript has been improved. I recommend that the editor accept the revised manuscript in its current form. Thank you, and congratulations to all the authors.

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