Validation performance comparison for finite element models of the human brain

Miller, Logan E.; Urban, Jillian E.; Stitzel, Joel D.

doi:10.1080/10255842.2017.1340462

Cited by 44 publications

(36 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the other extreme, (Sabet et al, 2008) used tagged MRI to measure 2D brain strains under low-rate head rotations in live humans. A representative parietal cadaveric impact (C291-T1; peak resultant linear/rotational acceleration magnitude of ~42.5 g/7.8 krad/s 2 ; acceleration profile relatively “clean” with one major acceleration peak; (Kleiven, 2006; Kleiven and Hardy, 2002; Miller et al, 2017) and an in vivo head rotation (~299 rad/s 2 ) were selected as input for model simulations. The time durations for the major acceleration peak in the two experiments were approximately 5 ms and 40 ms, respectively.…”

Section: Methodsmentioning

confidence: 99%

Material properties of the brain in injury-relevant conditions – Experiments and computational modeling

Zhao

Choate

2018

Journal of the Mechanical Behavior of Biomedical Materials

View full text Add to dashboard Cite

Material properties of the brain have been extensively studied but remain poorly characterized. The vast variations in constitutive models and material constants are well documented. However, no study exists to translate the variations into disparities in impact-induced brain strains most relevant to brain injury. Here, we reviewed a subset of injury-relevant brain material properties either characterized in experiments or adopted in recent head injury models. To highlight how variations in measured brain material properties manifested in simulated brain strains, we selected six experiments that have provided a complete set of brain material model and constants to implement a common head injury model. Responses resulting from two extreme events representing a high-rate cadaveric head impact and a low-rate in vivo head rotation, respectively, varied substantially. We hypothesized, and further confirmed, that the time-varying shear moduli at the appropriate time scales (e.g., ~5 ms and ~40 ms corresponding to the impulse durations of the major acceleration peaks for the two impacts, respectively), rather than the initial or long-term shear moduli, were the most indicative of impact-induced brain strains. These results underscored the need to implement measured brain material properties into an actual head injury model for evaluation. They may also provide guidelines to better characterize brain material properties in future experiments and head injury models. Finally, our finding provided a practical solution to satisfy head injury model validation requirements at both ends of the impact severity spectrum. This would improve the confidence in model simulation performance across a range of time scales relevant to concussion and sub-concussion in the real-world.

show abstract

Section: Methodsmentioning

confidence: 99%

Material properties of the brain in injury-relevant conditions – Experiments and computational modeling

Zhao

Choate

2018

Journal of the Mechanical Behavior of Biomedical Materials

View full text Add to dashboard Cite

show abstract

“…1) has been validated against brain displacement measurements in five cadaver impact experiments originally conducted by Hardy and coworkers (2001). 27,28 Impact locations…”

mentioning

confidence: 99%

Evaluation of Brain Response during Head Impact in Youth Athletes Using an Anatomically Accurate Finite Element Model

Miller

Urban

Kelley

et al. 2019

Journal of Neurotrauma

Self Cite

View full text Add to dashboard Cite

During normal participation in football, players are exposed to repetitive subconcussive head impacts, or impacts that do not result in signs and symptoms of concussion. To better understand the effects of repetitive subconcussive impacts, the biomechanics of on-field head impacts and resulting brain deformation need to be well characterized. The current study evaluates local brain response to typical youth football head impacts using the atlas-based brain model (ABM), an anatomically accurate brain finite element (FE) model. Head impact kinematic data were collected from three local youth football teams using the Head Impact Telemetry (HIT) System. The azimuth and elevation angles were used to identify impacts near six locations of interest, and low, moderate, and high acceleration magnitudes (5th, 50th, and 95th percentiles, respectively) were calculated from the grouped impacts for FE simulation. Strain response in the brain was evaluated by examining the range and peak maximum principal strain (MPS) values in each element. A total of 40,538 impacts from 119 individual athletes were analyzed. Impacts to the facemask resulted in 0.18 MPS for the high magnitude impact category. This was 1.5 times greater than the oblique impact location, which resulted in the lowest strain value of 0.12 for high magnitude impacts. Overall, higher strains resulted from a 95th percentile lateral impact (41.0g, 2556 rad/sec 2) with two predominant axes of rotation than from a 95th percentile frontal impact (67.6g, 2641 rad/sec 2) with a single predominant axis of rotation. These findings highlight the importance of accounting for directional dependence and relative contribution of axes of rotation when evaluating head impact response.

show abstract

“…15,23,40,41,45,51,53 Computational tools, such as finite element (FE) models, allow researchers to directly analyze the internal complex behavior of a system responsible for injury. 47,52 There are FE models of the human brain, 12,22,25,29,[31][32][33]46,55 full body, 10,18,24 and anthropomorphic test dummies (ATDs). 36,56 All these models can be used to study injury but in different ways.…”

Section: Introductionmentioning

confidence: 99%

Development and Multi-Scale Validation of a Finite Element Football Helmet Model

Decker

Baker

et al. 2019

Ann Biomed Eng

View full text Add to dashboard Cite

Head injury is a growing concern within contact sports, including American football. Computational tools such as finite element (FE) models provide an avenue for researchers to study, and potentially optimize safety tools, such as helmets. The goal of this study was to develop an accurate representative helmet model that could be used in further study of head injury to mitigate the toll of concussions in contact sports. An FE model of a Schutt Air XP Pro football helmet was developed through three major steps: geometry development, material characterization, and model validation. The fully assembled helmet model was fit onto a Hybrid III dummy head–neck model and National Operating Committee on Standards for Athletic Equipment (NOCSAE) head model and validated through a series of 67 representative impacts similar to those experienced by a football player. The kinematic and kinetic response of the model was compared to the response of the physical experiments, which included force, head linear acceleration, head angular velocity, and carriage acceleration. The outputs between the model and the physical tests were quantitatively evaluated using CORelation and Analysis (CORA), amounting to an overall averaged score of 0.76. The model described in this study has been extensively validated and can function as a building block for innovation in player safety.

show abstract

Validation performance comparison for finite element models of the human brain

Cited by 44 publications

References 35 publications

Material properties of the brain in injury-relevant conditions – Experiments and computational modeling

Material properties of the brain in injury-relevant conditions – Experiments and computational modeling

Evaluation of Brain Response during Head Impact in Youth Athletes Using an Anatomically Accurate Finite Element Model

Development and Multi-Scale Validation of a Finite Element Football Helmet Model

Contact Info

Product

Resources

About