Skip to content

Head

  • Trotta, 20201: Biofidelic finite element modelling of brain trauma: Importance of the scalp in simulating head impact

  • Bruneau, 20192: Head and Neck Response of an Active Human Body Model and Finite Element Anthropometric Test Device During a Linear Impactor Helmet Test

Although responses that develop over longer durations following the impact differed slightly, such as the moment at the base of the neck, this occurred later in time, and therefore, did not considerably affect the short-term head kinematics in the primary impact direction. Though muscle activation did not play a strong role in the head response for the test configurations considered, muscle activation may play a role in longer duration events.

  • @Miller2019: An envelope of linear and rotational head motion during everyday activities

The peak resultant linear accelerations of the head reported in the literature were all less than 15 g, while the peak resultant rotational accelerations and rotational velocities approach 1375 rad/s2 and 12.8 rad/s, respectively.

  • @Chang2019: Evaluation of Human Nasal Cartilage Nonlinear and Rate Dependent Mechanical Properties

  • @Yoganandan2009: Neck Forces and Moments and Head Accelerations in Side Impact

Skull

  • Zhou, 20203: Evaluation of brain-skull interface modelling approaches on the prediction of acute subdural hematoma in the elderly

Brain

  • Gabrieli, 20204: A Multibody Model for Predicting Spatial Distribution of Human Brain Deformation Following Impact Loading

  • Alshareef, 20205: Biomechanics of the Human Brain during Dynamic Rotation of the Head

  • Hajiaghamemar, 20196: Embedded axonal fiber tracts improve finite element model predictions of traumatic brain injury

  • Budday, 20197: Challenges and perspectives in brain tissue testing and modeling

Models

  • Wang, 20188: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model, Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact (THUMS4)

The brain–skull interface models included direct representation of the brain meninges and cerebrospinal fluid, outer brain surface rigidly attached to the skull, frictionless sliding contact between the brain and skull, and a layer of spring-type cohesive elements between the brain and skull. We considered Ogden hyperviscoelastic, Mooney–Rivlin hyperviscoelastic, neo–Hookean hyperviscoelastic and linear viscoelastic constitutive models of the brain tissue. Our study indicates that the predicted deformations within the brain and related brain injury criteria are strongly affected by both the approach of modelling the brain–skull interface and the constitutive model of the brain parenchyma tissues.

Experiments

  • @Li2019: A Comprehensive Study on the Mechanical Properties of Different Regions of 8-week-old Pediatric Porcine Brain under Tension, Shear, and Compression at Various Strain Rates

Sports

  • @Kent2019: The Biomechanics of Concussive Helmet-to-Ground Impacts in the National Football League

Video analysis was performed for 16 head-to-ground impacts that caused concussions. Average resultant closing velocity was 8.3 m/s at an angle nearly 45° to the surface. Preimpact rotational velocity of the helmet ranged from negligible to as high as 54.1 rad/s. Helmet impacts were concentrated on the posterior and lateral aspects.

  1. Antonia Trotta, J. Michio Clark, Adrian McGoldrick, Michael D Gilchrist, and Aisling N\'ı Annaidh. Biofidelic finite element modelling of brain trauma: importance of the scalp in simulating head impact. International Journal of Mechanical Sciences, 173:105448, may 2020. doi:10.1016/j.ijmecsci.2020.105448. ↩

  2. David A. Bruneau and Duane S. Cronin. Head and neck response of an active human body model and finite element anthropometric test device during a linear impactor helmet test. Journal of Biomechanical Engineering, oct 2019. doi:10.1115/1.4043667. ↩

  3. Zhou Zhou, Xiaogai Li, and Svein Kleiven. Evaluation of brain-skull interface modelling approaches on the prediction of acute subdural hematoma in the elderly. Journal of Biomechanics, pages 109787, apr 2020. doi:10.1016/j.jbiomech.2020.109787. ↩

  4. David Gabrieli, Nicholas Vigilante, Richard Scheinfield, Jared A Rifkin, Samantha Schumm, Taotao Wu, Lee Gabler, Matthew Panzer, and David F. Meaney. A multibody model for predicting spatial distribution of human brain deformation following impact loading. Journal of Biomechanical Engineering, apr 2020. doi:10.1115/1.4046866. ↩

  5. Ahmed Alshareef, J. Sebastian Giudice, Jason Forman, Daniel F. Shedd, Kristen A. Reynier, Taotao Wu, Sara Sochor, Mark R. Sochor, Robert S. Salzar, and Matthew B. Panzer. Biomechanics of the human brain during dynamic rotation of the head. Journal of Neurotrauma, mar 2020. doi:10.1089/neu.2019.6847. ↩

  6. Marzieh Hajiaghamemar, Taotao Wu, Matthew B. Panzer, and Susan S. Margulies. Embedded axonal fiber tracts improve finite element model predictions of traumatic brain injury. Biomechanics and Modeling in Mechanobiology, dec 2019. doi:10.1007/s10237-019-01273-8. ↩

  7. Silvia Budday, Gerhard A. Holzapfel, Paul Steinmann, and Ellen Kuhl. Challenges and perspectives in brain tissue testing and modeling. PAMM, nov 2019. doi:10.1002/pamm.201900269. ↩

  8. Fang Wang, Yong Han, Bingyu Wang, Qian Peng, Xiaoqun Huang, Karol Miller, and Adam Wittek. Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model. Biomechanics and Modeling in Mechanobiology, 174:1165–1185, may 2018. doi:10.1007/s10237-018-1021-z. ↩