ArticleAnnals of biomedical engineering2015
A Pre-computed Brain Response Atlas for Instantaneous Strain Estimation in Contact Sports.
Article in Annals of biomedical engineering, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 53 citations in OpenAlex.
- Data-driven standards for infant skull thickness distributions in computational modeling and analysis.Journal of anatomy · 2025Article
- Efficient Generation of Pretraining Samples for Developing a Deep Learning Brain Injury Model via Transfer Learning.Annals of biomedical engineering · 2024Article
- The Impact of Drop Test Conditions on Brain Strain Location and Severity: A Novel Approach Using a Deep Learning Model.Annals of biomedical engineering · 2024Article
- American Football On-Field Head Impact Kinematics: Influence of Acceleration Signal Characteristics on Peak Maximal Principal Strain.Annals of biomedical engineering · 2024Article
- Drop Test Kinematics Using Varied Impact Surfaces and Head/Neck Configurations for Rugby Headgear Testing.Annals of biomedical engineering · 2022Article
- Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports.Annals of biomedical engineering · 2022Review
- Real-time dynamic simulation for highly accurate spatiotemporal brain deformation from impact.Computer methods in applied mechanics and engineering · 2022Article
- [Evaluation of brain injury caused by stick type blunt instruments based on convolutional neural network and finite element method].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022Article
- MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury.Annals of biomedical engineering · 2021Review
- Instantaneous Whole-Brain Strain Estimation in Dynamic Head Impact.Journal of neurotrauma · 2021Article
- A machine learning approach for magnetic resonance image-based mouse brain modeling and fast computation in controlled cortical impact.Medical & biological engineering & computing · 2020Article
- An envelope of linear and rotational head motion during everyday activities.Biomechanics and modeling in mechanobiology · 2020Article
- Low-Rank Representation of Head Impact Kinematics: A Data-Driven Emulator.Frontiers in bioengineering and biotechnology · 2020Article
- Convolutional neural network for efficient estimation of regional brain strains.Scientific reports · 2019Article
- Evaluation of Brain Response during Head Impact in Youth Athletes Using an Anatomically Accurate Finite Element Model.Journal of neurotrauma · 2019Article
- Mesh Convergence Behavior and the Effect of Element Integration of a Human Head Injury Model.Annals of biomedical engineering · 2019Article
- White Matter Anisotropy for Impact Simulation and Response Sampling in Traumatic Brain Injury.Journal of neurotrauma · 2019Article
- Material properties of the brain in injury-relevant conditions - Experiments and computational modeling.Journal of the mechanical behavior of biomedical materials · 2018Article
- Performance Evaluation of a Pre-computed Brain Response Atlas in Dummy Head Impacts.Annals of biomedical engineering · 2017Article
- Injury prediction and vulnerability assessment using strain and susceptibility measures of the deep white matter.Biomechanics and modeling in mechanobiology · 2017Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Finite element models of the human head play an important role in investigating the mechanisms of traumatic brain injury, including sports concussion. A critical limitation, however, is that they incur a substantial computational cost to simulate even a single impact. Therefore, current simulation schemes significantly hamper brain injury studies based on model-estimated tissue-level responses. In this study, we present a pre-computed brain response atlas (pcBRA) to substantially increase the simulation efficiency in estimating brain strains using isolated rotational acceleration impulses parameterized with four independent variables (peak magnitude and duration, and rotational axis azimuth and elevation angles) with values determined from on-field measurements. Using randomly generated testing datasets, the partially established pcBRA achieved a 100% success rate in interpolation based on element-wise differences in accumulated peak strain ([Formula: see text]) according to a "double-10%" criterion or average regional [Formula: see text] in generic regions and the corpus callosum. A similar performance was maintained in extrapolation. The pcBRA performance was further successfully validated against directly simulated responses from two independently measured typical real-world rotational profiles. The computational cost to estimate element-wise whole-brain or regional [Formula: see text] was 6 s and <0.01 s, respectively, vs. ~50 min directly simulating a 40 ms impulse. These findings suggest the pcBRA could substantially increase the throughput in impact simulation without significant loss of accuracy from the estimation itself and, thus, its potential to accelerate the exploration of the mechanisms of sports concussion in general. If successful, the pcBRA may also become a diagnostic adjunct in conjunction with sensors that measure head impact kinematics on the field to objectively monitor and identify tissue-level brain trauma in real-time for "return-to-play" decision-making on the sideline.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.