Sporting helmets with linear attenuating strategies are proficient at reducing the risk of traumatic brain injury. However, the continued high incidence of concussion in American football, has led researchers to investigate novel helmet liner strategies. These strategies typically supplement existing technologies by adding or integrating head-helmet decoupling mechanisms. Decoupling strategies aim to redirect or redistribute impact force around the head, reducing impact energy transferred to the brain. This results in decreased brain tissue strain, which is beneficial in injury risk reduction due to the link between tissue strain and concussive injury.The purpose of this study was to mathematically demonstrate the effect of ten cases, representing theoretical redirection and redistribution helmet liner strategies, on brain tissue strain resulting from impacts to the head. The kinematic response data from twenty head impacts collected in the laboratory was mathematically modified to represent the altered response of the ten different cases and used as input parameters to determine the effect on maximum principal strain (MPS) values, calculated using finite element modeling. The results showed that a reduced dominant coordinate component (contributes the greatest to resultant) of rotational acceleration decreased maximum principal strain in American football helmets. The study theoretically demonstrates that liner strategies, if applied correctly, can influence brain motion, reduce brain tissue strain, and could decrease injury risk in an American football helmet.
Background Falls are a common cause of morbidity and mortality in society, particularly among the aged and young. There has been research to describe the epidemiology of these types of events, but to date there has been few correlations of clinical brain injury outcomes and metrics used in biomechanical research; parameters often used to help develop protective devices and environments. The purpose of this research was to examine the kinematic characteristics of falls from standing and higher heights in an effort to understand how clinical brain injury is predicted by biomechanical injury metrics. Methods Computer simulations of nine traumatic brain injury events from falling were conducted to determine the biomechanical metrics associated with each injury case. Results Many of the impacts were to the occipital region of the head, as would be expected from backward falls or from slipping from ladders. These falls resulted in low rotational acceleration values and high linear accelerations, suggesting linear acceleration may be an important characteristic of this injury mechanism. In addition, even though each case resulted in severe head injury, the HIC 15 (Head Injury Criterion) values did not consistently predict injury when the kinematic output was lower than 300 g. This result suggests that HIC 15 may have limited value as a predictor for high energy short duration direct impacts to the head. The results supported a relationship between fall height and duration of loss of consciousness, with the higher fall heights producing longer times of unconsciousness. Conclusion Linear acceleration may be the metric that should be focused on to develop further strategies to protect against severe TBI for fall cases similar to those in this research. In addition, the HIC 15 may not be suitable as a predictive metric for TBI and future development of protective devices for the prevention of head injury should take this into account.
Impact parameters used to design the American football helmet and the parameters associated with mechanisms of concussive injury are not consistent. Head impacts resulting in concussive injury in football are characterized as events creating rotational motion of the head that generate brain tissue strain. The extent of tissue strain influences the resulting severity of injury. Helmet technology aimed to decrease brain tissue strain by reducing the extent of brain motion could help reduce injury risk. Current helmet performance and evaluation measures, such as peak resultant of linear and rotational acceleration, do not fully define directional brain motion and therefore cannot provide sufficient information for this type of improvement. This study was conducted to determine whether coordinate components (X, Y, and Z) of linear and rotational acceleration would correlate with maximum principal strain, a common measure of brain injury risk. Coordinate components define directional motion of the head and offer a specific design parameter more easily reduced using engineered structures than peak resultant acceleration. In addition to coordinate components, this study introduces the dominant component, defined as the coordinate component with the highest contribution to the resultant acceleration, for additional evaluation. The results show that the relationship between the X, Y, and Z coordinate components of acceleration and maximum principal strain is location- and direction-dependent. The study indicates a strong relationship between the peak resultant and dominant components of acceleration to maximum principal strain. Because the dominant component of acceleration accounts for direction and location, identifying the relationship between dominant acceleration and maximum principal strain demonstrates the potential use of this metric to improve future helmet innovation aimed at reducing tissue strain.
This research focuses on describing the differences between mild traumatic brain injury (mTBI) and focal traumatic brain injury (fTBI). The purpose of this research was to compare clinical mTBI and fTBI groups who incurred brain injury from falls to hard surfaces to identify clinical and biomechanical factors that may delineate between these two outcomes. Reconstructions of mTBI (n = 11) and fTBI (n = 20) cases that resulted from falls presented themselves at the hospital were conducted using computational and physical models. The cases were compared using peak and component dynamic response, brain injury criterion (BrIC), Gadd severity index and head injury criterion. Peak resultant rotational acceleration had the best percentage correct classification with 50% risk of severe TBI was found to be 21 krad/s2. The BrIC and component acceleration and rotational velocity of impact were also found to have significant predictions of risk between the two groups. This data provides information to improve risk thresholds for fTBI with application to helmet standards/development.
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