Skip to main content

Advertisement

Log in

Nano-Composite Foam Sensor System in Football Helmets

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

American football has both the highest rate of concussion incidences as well as the highest number of concussions of all contact sports due to both the number of athletes and nature of the sport. Recent research has linked concussions with long term health complications such as chronic traumatic encephalopathy and early onset Alzheimer’s. Understanding the mechanical characteristics of concussive impacts is critical to help protect athletes from these debilitating diseases and is now possible using helmet-based sensor systems. To date, real time on-field measurement of head impacts has been almost exclusively measured by devices that rely on accelerometers or gyroscopes attached to the player’s helmet, or embedded in a mouth guard. These systems monitor motion of the head or helmet, but do not directly measure impact energy. This paper evaluates the accuracy of a novel, multifunctional foam-based sensor that replaces a portion of the helmet foam to measure impact. All modified helmets were tested using a National Operating Committee Standards for Athletic Equipment-style drop tower with a total of 24 drop tests (4 locations with 6 impact energies). The impacts were evaluated using a headform, instrumented with a tri-axial accelerometer, mounted to a Hybrid III neck assembly. The resultant accelerations were evaluated for both the peak acceleration and the severity indices. These data were then compared to the voltage response from multiple Nano Composite Foam sensors located throughout the helmet. The foam sensor system proved to be accurate in measuring both the HIC and Gadd severity index, as well as peak acceleration while also providing additional details that were previously difficult to obtain, such as impact energy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

References

  1. Allison, M. A., et al. Validation of a helmet-based system to measure head impact biomechanics in ice hockey. Med. Sci. Sports Exerc. 46(1):115–123, 2014.

    Article  PubMed  Google Scholar 

  2. Buzzini, S. R. R., and K. M. Guskiewicz. Sport-related concussion in the young athlete. Curr. Opin. Pediatr. 18(4):376–382, 2006.

    Article  PubMed  Google Scholar 

  3. Camarillo, D. B., et al. An instrumented mouthguard for measuring linear and angular head impact kinematics in American football. Ann. Biomed. Eng. 41(9):1939–1949, 2013.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Campbell, K. R., et al. Laboratory evaluation of the gForce Tracker™, a head impact kinematic measuring device for use in football helmets. Ann. Biomed. Eng. 44(4):1246–1256, 2016.

    Article  PubMed  Google Scholar 

  5. Conidi, F. X. Helmets, sensors, and more: a review. Pract. Neurol. 15(2):32–36, 2015.

    Google Scholar 

  6. Crisco, J. J., et al. Frequency and location of head impact exposures in individual collegiate football players. J. Athl. Train. 45(6):549–559, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Crisco, J. J., et al. Head impact exposure in collegiate football players. J. Biomech. 44(15):2673–2678, 2011.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Daniel, R. W., S. Rowson, and S. M. Duma. Head impact exposure in youth football. Ann. Biomed. Eng. 40:976–981, 2012.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Duma, S. M., et al. Analysis of real-time head accelerations in collegiate football players. Clin. J. Sport Med. 15:3–8, 2005.

    Article  PubMed  Google Scholar 

  10. Duma, S. M., et al. Analysis of real-time head accelerations in collegiate football players. Clin. J. Sport Med. 15(1):3–8, 2005.

    Article  PubMed  Google Scholar 

  11. Fainaru-Wada, M., and S. Fainaru. League of Denial: The NFL, Concussions, and the Battle for Truth. New York: Three Rivers Press, 2013.

    Google Scholar 

  12. Foster, J. K., J. O. Kortge, and M. J. Wolanin. Hybrid III-A Biomechanically-Based Crash Test Dummy. SAE International, 1977.

  13. Funk, J. R., et al. Biomechanical Risk Estimates for Mild Traumatic Brain Injury. Annual proceedings/Association for the Advancement of Automotive Medicine. Association for the Advancement of Automotive Medicine, vol. 51, pp. 343–361, 2007.

  14. Funk, J. R., et al. Validation of concussion risk curves for collegiate football players derived from HITS data. Ann. Biomed. Eng. 40(1):79–89, 2012.

    Article  PubMed  Google Scholar 

  15. Gadd, C. W. Use of a Weighted-Impulse Criterion for Estimating Injury Hazard. SAE Technical Paper, 1966.

  16. Gurdjian, E. S., V. Roberts, and L. M. Thomas. Tolerance curves of acceleration and intracranial pressure and protective index in experimental head injury. J. Trauma Acute Care Surg. 6(5):600–604, 1966.

    Article  CAS  Google Scholar 

  17. Gurdjian, E., et al. Quantitative determination of acceleration and intracranial pressure in experimental head injury preliminary report. Neurology 3(6):417, 1953.

    Article  CAS  PubMed  Google Scholar 

  18. Gurdjian, E. S., et al. Evaluation of the protective characteristics of helmets in sports. J. Trauma Acute Care Surg. 4(3):309–324, 1964.

    Article  CAS  Google Scholar 

  19. Guskiewicz, K. M., and J. P. Mihalik. Biomechanics of sport concussion: quest for the elusive injury threshold. Exerc. Sport Sci. Rev. 39(1):4–11, 2011.

    Article  PubMed  Google Scholar 

  20. Guskiewicz, K. M., et al. Cumulative effects associated with recurrent concussion in collegiate football players—the NCAA concussion study. JAMA 290(19):2549–2555, 2003.

    Article  CAS  PubMed  Google Scholar 

  21. Guskiewicz, K. M., et al. Association between recurrent concussion and late-life cognitive impairment in retired professional football players. Neurosurgery 57(4):719–724, 2005.

    Article  PubMed  Google Scholar 

  22. Guskiewicz, K. M., et al. Recurrent concussion and risk of depression in retired professional football players. Med. Sci. Sports Exerc. 39(6):903–909, 2007.

    Article  PubMed  Google Scholar 

  23. Hanlon, E. M., and C. A. Bir. Real-time head acceleration measurement in girls’ youth soccer. Med. Sci. Sports Exercise 44(6):1102–1108, 2012.

    Article  Google Scholar 

  24. Hernandez, F., et al. Six degree-of-freedom measurements of human mild traumatic brain injury. Ann. Biomed. Eng. 43(8):1918–1934, 2015.

    Article  PubMed  Google Scholar 

  25. Higgins, M., et al. Measurement of impact acceleration: mouthpiece accelerometer versus helmet accelerometer. J. Athl. Train. 42(1):5–10, 2007.

    PubMed  PubMed Central  Google Scholar 

  26. Hutchinson, J., M. J. Kaiser, and H. M. Lankarani. The head injury criterion (HIC) functional. Appl. Math. Comput. 96(1):1–16, 1998.

    Article  Google Scholar 

  27. Jadischke, R., et al. On the accuracy of the Head Impact Telemetry (HIT) System used in football helmets. J. Biomech. 46(13):2310–2315, 2013.

    Article  PubMed  Google Scholar 

  28. Knox, T., et al. New Sensors to Track Head Acceleration during Possible Injurious Events. DTIC Document, 2009.

  29. Manoogian, S., et al. Head acceleration is less than 10 percent of helmet acceleration during a football impact. Biomed. Sci. Instrum. 42:383–388, 2006.

    PubMed  Google Scholar 

  30. Marar, M., et al. Epidemiology of concussions among United States high school athletes in 20 sports. Am. J. Sports Med. 40(4):747–755, 2012.

    Article  PubMed  Google Scholar 

  31. Miyashita, T., et al. Frequency and Location of Head Impacts in Division I Men’s Lacrosse Players. Athletic Training and Sports Health Care, 2016.

  32. NOCSAE. Standard Performance Specification for Newly Manufactured Football Helmets. National Operating Committee on Standards for Athletic Equipment, 2014.

  33. NOCSAE. Standard Test Method and Equipment Used in Evaluating the Performance Characteristics of Protective Headgear/Equipment, 2015.

  34. Olvey, S. E., T. Knox, and K. A. Cohn. The development of a method to measure head acceleration and motion in high-impact crashes. Neurosurgery 54(3):672–677, 2004.

    Article  PubMed  Google Scholar 

  35. Patel, D. R., and D. E. Greydanus. Neurologic considerations for adolescent athletes. Adolesc. Med. Clin. 13(3):569, 2002.

    Google Scholar 

  36. Patel, D. R., V. Shivdasani, and R. J. Baker. Management of sport-related concussion in young athletes. Sports Med. 35(8):671–684, 2005.

    Article  PubMed  Google Scholar 

  37. Rowson, S., and S. M. Duma. Development of the STAR evaluation system for football helmets: integrating player head impact exposure and risk of concussion. Ann. Biomed. Eng. 39(8):2130–2140, 2011.

    Article  PubMed  Google Scholar 

  38. Rowson, S., et al. A six degree of freedom head acceleration measurement device for use in football. J. Appl. Biomech. 27(1):8–14, 2011.

    Article  PubMed  Google Scholar 

  39. Rowson, S., et al. Can helmet design reduce the risk of concussion in football? J. Neurosurg. 120(4):919–922, 2014.

    Article  PubMed  Google Scholar 

  40. Siegmund, G. P., et al. Laboratory validation of two wearable sensor systems for measuring head impact severity in football players. Ann. Biomed. Eng. 44(4):1257–1274, 2016.

    Article  PubMed  Google Scholar 

  41. Tianyi, F.-L., V. N. Agbor, and T. Njim. Motorbike-handlebar hernia-a rare traumatic abdominal wall hernia: a case report and review of the literature. J. Med. Case Rep. 11(1):87, 2017.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Versace, J. A Review of the Severity Index. SAE Technical Paper, 1971.

  43. Wojtowicz, M., et al. Consistency of self-reported concussion history in adolescent athletes. J. Neurotrauma 34(2):322–327, 2017.

    Article  PubMed  Google Scholar 

  44. Wu, L. C., et al. A head impact detection system using SVM classification and proximity sensing in an instrumented mouthguard. IEEE Trans. Biomed. Eng. 61(11):2659–2668, 2014.

    Article  PubMed  Google Scholar 

  45. Young, T. J., et al. Head impact exposure in youth football: elementary school ages 7-8 years and the effect of returning players. Clin. J. Sport Med. 24(5):416–421, 2014.

    Article  PubMed  Google Scholar 

  46. Zanetti, E. M., et al. Amateur football pitches: mechanical properties of the natural ground and of different artificial turf infills and their biomechanical implications. J. Sports Sci. 31(7):767–778, 2013.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This material and research are based upon work supported by the National Science Foundation under Grant Numbers CMMI-1538447 and IIP1549719. All helmet testing was performed at Virginia Polytechnic Institute and State University’s Biomedical Engineering and Mechanics helmet testing lab.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Jake Merrell.

Additional information

Associate Editor Karol Miller oversaw the review of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Merrell, A.J., Christensen, W.F., Seeley, M.K. et al. Nano-Composite Foam Sensor System in Football Helmets. Ann Biomed Eng 45, 2742–2749 (2017). https://doi.org/10.1007/s10439-017-1910-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-017-1910-9

Keywords

Navigation