Nano-Composite Foam Sensor System in Football Helmets
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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.
KeywordsFootball helmet Impact detection Piezoelectric foam Self-sensing foam Impact energy Impact velocity Acceleration Severity index
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.
- 5.Conidi, F. X. Helmets, sensors, and more: a review. Pract. Neurol. 15(2):32–36, 2015.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.Google Scholar
- 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.Google Scholar
- 15.Gadd, C. W. Use of a Weighted-Impulse Criterion for Estimating Injury Hazard. SAE Technical Paper, 1966.Google Scholar
- 28.Knox, T., et al. New Sensors to Track Head Acceleration during Possible Injurious Events. DTIC Document, 2009.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.Google Scholar
- 32.NOCSAE. Standard Performance Specification for Newly Manufactured Football Helmets. National Operating Committee on Standards for Athletic Equipment, 2014.Google Scholar
- 33.NOCSAE. Standard Test Method and Equipment Used in Evaluating the Performance Characteristics of Protective Headgear/Equipment, 2015.Google Scholar
- 35.Patel, D. R., and D. E. Greydanus. Neurologic considerations for adolescent athletes. Adolesc. Med. Clin. 13(3):569, 2002.Google Scholar
- 42.Versace, J. A Review of the Severity Index. SAE Technical Paper, 1971.Google Scholar