Aomura, S; Zhang, Y; Nakadate, H; Koyama, T; Nishimura, A
Brain injury risk estimation of collegiate football player based on game video of concussion suspected accident Journal Article
In: Journal of Biomechanical Science and Engineering, vol. 11, no. 4, 2016.
Abstract | Links | BibTeX | Tags: Accidents, Brain Injury, Brain injury risk estimation, Collision accidents, DIAGNOSIS, FEM, Finite element method, FOOTBALL players, Game video, Game videos, Health risks, Initial conditions, Mechanical parameters, Motion analysis, Relative positions, RISK assessment, Risk perception, Rotational velocity, Sports, Sports-related concussion
@article{Aomura2016,
title = {Brain injury risk estimation of collegiate football player based on game video of concussion suspected accident},
author = {Aomura, S and Zhang, Y and Nakadate, H and Koyama, T and Nishimura, A},
doi = {10.1299/jbse.16-00393},
year = {2016},
date = {2016-01-01},
journal = {Journal of Biomechanical Science and Engineering},
volume = {11},
number = {4},
abstract = {The collision accident in collegiate football game was simulated based on the game video and the concussive impact on the head was analyzed. First, the collision motion of players was reproduced based on the video by using motion analysis, and the translational and rotational velocities, relative position and contact location of the struck and the striking players' heads just before the collision were calculated. Then the data obtained were input to two helmeted finite element (FE) human head models as the initial condition, and the brain injury risk was evaluated by using the impact analysis. The FE helmet model was validated by a drop test of the helmet in which the head impactor was embedded. In the present study, two concussion suspected accident cases were analyzed; then the concussion was evaluated by ten mechanical parameters generated inside the skull caused by the collision. The injury risk evaluated by multi parameters belonged to the dangerous range that may cause concussion and was consistent with the diagnosis of the medical team doctor. The brain injury risk can be successfully estimated by the reconstructed simulation of the game video and FE analysis. To our knowledge, this study is the first attempt in Japan to estimate the brain injury risk systematically by a combination of game video analysis which is originally introduced for the players' health care and FE analysis by helmeted human head model. In the future, brain injury risk caused by an accident can be evaluated with higher accuracy by analyzing more accident cases. © 2016 The Japan Society of Mechanical Engineers.},
keywords = {Accidents, Brain Injury, Brain injury risk estimation, Collision accidents, DIAGNOSIS, FEM, Finite element method, FOOTBALL players, Game video, Game videos, Health risks, Initial conditions, Mechanical parameters, Motion analysis, Relative positions, RISK assessment, Risk perception, Rotational velocity, Sports, Sports-related concussion},
pubstate = {published},
tppubtype = {article}
}
Johnson, K L; Chowdhury, S; Lawrimore, W B; Mao, Y; Mehmani, A; Prabhu, R; Rush, G A; Horstemeyer, M F
Constrained topological optimization of a football helmet facemask based on brain response Journal Article
In: Materials and Design, vol. 111, pp. 108–118, 2016.
Abstract | Links | BibTeX | Tags: Accident prevention, ALGORITHMS, brain, Concussion, Constrained optimization, Design, Design optimization, finite element analysis, Finite element method, football helmet, Fuel additives, Genetic algorithms, Multiobjective optimization, Optimization, Safety devices, Shear strain, Sports, Surrogate model, Surrogate modeling, Topology, Traumatic Brain Injuries, traumatic brain injury
@article{Johnson2016a,
title = {Constrained topological optimization of a football helmet facemask based on brain response},
author = {Johnson, K L and Chowdhury, S and Lawrimore, W B and Mao, Y and Mehmani, A and Prabhu, R and Rush, G A and Horstemeyer, M F},
doi = {10.1016/j.matdes.2016.08.064},
year = {2016},
date = {2016-01-01},
journal = {Materials and Design},
volume = {111},
pages = {108--118},
abstract = {Surrogate model-based multi-objective design optimization was performed to reduce concussion risk during frontal football helmet impacts. In particular, a topological decomposition of the football helmet facemask was performed to formulate the design problem, and brain injury metrics were exploited as objective functions. A validated finite element model of a helmeted human head was used to recreate facemask impacts. Due to the prohibitive computational expense of the full scale simulations, a surrogate modeling approach was employed. An optimal surrogate model selection framework, called Concurrent Surrogate Model Selection, or COSMOS, was utilized to identify the surrogate models best suited to approximate each objective function. The resulting surrogate models were implemented in the Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization algorithm. Constraints were implemented to control the solid material fraction in the facemask design space, and binary variables were used to control the placement of the facemask bars. The optimized facemask designs reduced the maximum tensile pressure in the brain by 7.5% and the maximum shear strain by a remarkable 39.5%. This research represents a first-of-its-kind approach to multi-objective design optimization on a football helmet, and demonstrates the possibilities that are achievable in improving human safety by using such a simulation-based design optimization. © 2016 Elsevier Ltd},
keywords = {Accident prevention, ALGORITHMS, brain, Concussion, Constrained optimization, Design, Design optimization, finite element analysis, Finite element method, football helmet, Fuel additives, Genetic algorithms, Multiobjective optimization, Optimization, Safety devices, Shear strain, Sports, Surrogate model, Surrogate modeling, Topology, Traumatic Brain Injuries, traumatic brain injury},
pubstate = {published},
tppubtype = {article}
}
Patton, D A; McIntosh, A S; Kleiven, S
In: Journal of Applied Biomechanics, vol. 31, no. 4, pp. 264–268, 2015.
Abstract | Links | BibTeX | Tags: Article, Biomechanics, brain, Brain Injury, brain region, clinical article, Concussion, corpus callosum, Damage detection, evaluation study, finite element analysis, Finite element head models, Finite element method, Finite element simulations, football, gray matter, Head Injuries, head injury, human, Intra-cranial pressure, intracranial pressure, investigative procedures, Maximum principal strain, mesencephalon, Modeling, Models, Numerical reconstruction, Qualitative observations, Sport, sport injury, Sports, Strain and strain rates, Strain rate, Stress, thalamus, Tissue, tissue level
@article{Patton2015,
title = {The biomechanical determinants of concussion: Finite element simulations to investigate tissue-level predictors of injury during sporting impacts to the unprotected head},
author = {Patton, D A and McIntosh, A S and Kleiven, S},
doi = {10.1123/jab.2014-0223},
year = {2015},
date = {2015-01-01},
journal = {Journal of Applied Biomechanics},
volume = {31},
number = {4},
pages = {264--268},
abstract = {Biomechanical studies of concussions have progressed from qualitative observations of head impacts to physical and numerical reconstructions, direct impact measurements, and finite element analyses. Supplementary to a previous study, which investigated maximum principal strain, the current study used a detailed finite element head model to simulate unhelmeted concussion and no-injury head impacts and evaluate the effectiveness of various tissue-level brain injury predictors: strain rate, product of strain and strain rate, cumulative strain damage measure, von Mises stress, and intracranial pressure. Von Mises stress was found to be the most effective predictor of concussion. It was also found that the thalamus and corpus callosum were brain regions with strong associations with concussion. Tentative tolerance limits for tissue-level predictors were proposed in an attempt to broaden the understanding of unhelmeted concussions. For the thalamus, tolerance limits were proposed for a 50% likelihood of concussion: 2.24 kPa, 24.0 s-1, and 2.49 s-1 for von Mises stress, strain rate, and the product of strain and strain rate, respectively. For the corpus callosum, tolerance limits were proposed for a 50% likelihood of concussion: 3.51 kPa, 25.1 s-1, and 2.76 s-1 for von Mises stress, strain rate, and the product of strain and strain rate, respectively. © 2015 Human Kinetics, Inc.},
keywords = {Article, Biomechanics, brain, Brain Injury, brain region, clinical article, Concussion, corpus callosum, Damage detection, evaluation study, finite element analysis, Finite element head models, Finite element method, Finite element simulations, football, gray matter, Head Injuries, head injury, human, Intra-cranial pressure, intracranial pressure, investigative procedures, Maximum principal strain, mesencephalon, Modeling, Models, Numerical reconstruction, Qualitative observations, Sport, sport injury, Sports, Strain and strain rates, Strain rate, Stress, thalamus, Tissue, tissue level},
pubstate = {published},
tppubtype = {article}
}
Aomura, S; Zhang, Y; Nakadate, H; Koyama, T; Nishimura, A
Brain injury risk estimation of collegiate football player based on game video of concussion suspected accident Journal Article
In: Journal of Biomechanical Science and Engineering, vol. 11, no. 4, 2016.
@article{Aomura2016,
title = {Brain injury risk estimation of collegiate football player based on game video of concussion suspected accident},
author = {Aomura, S and Zhang, Y and Nakadate, H and Koyama, T and Nishimura, A},
doi = {10.1299/jbse.16-00393},
year = {2016},
date = {2016-01-01},
journal = {Journal of Biomechanical Science and Engineering},
volume = {11},
number = {4},
abstract = {The collision accident in collegiate football game was simulated based on the game video and the concussive impact on the head was analyzed. First, the collision motion of players was reproduced based on the video by using motion analysis, and the translational and rotational velocities, relative position and contact location of the struck and the striking players' heads just before the collision were calculated. Then the data obtained were input to two helmeted finite element (FE) human head models as the initial condition, and the brain injury risk was evaluated by using the impact analysis. The FE helmet model was validated by a drop test of the helmet in which the head impactor was embedded. In the present study, two concussion suspected accident cases were analyzed; then the concussion was evaluated by ten mechanical parameters generated inside the skull caused by the collision. The injury risk evaluated by multi parameters belonged to the dangerous range that may cause concussion and was consistent with the diagnosis of the medical team doctor. The brain injury risk can be successfully estimated by the reconstructed simulation of the game video and FE analysis. To our knowledge, this study is the first attempt in Japan to estimate the brain injury risk systematically by a combination of game video analysis which is originally introduced for the players' health care and FE analysis by helmeted human head model. In the future, brain injury risk caused by an accident can be evaluated with higher accuracy by analyzing more accident cases. © 2016 The Japan Society of Mechanical Engineers.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Johnson, K L; Chowdhury, S; Lawrimore, W B; Mao, Y; Mehmani, A; Prabhu, R; Rush, G A; Horstemeyer, M F
Constrained topological optimization of a football helmet facemask based on brain response Journal Article
In: Materials and Design, vol. 111, pp. 108–118, 2016.
@article{Johnson2016a,
title = {Constrained topological optimization of a football helmet facemask based on brain response},
author = {Johnson, K L and Chowdhury, S and Lawrimore, W B and Mao, Y and Mehmani, A and Prabhu, R and Rush, G A and Horstemeyer, M F},
doi = {10.1016/j.matdes.2016.08.064},
year = {2016},
date = {2016-01-01},
journal = {Materials and Design},
volume = {111},
pages = {108--118},
abstract = {Surrogate model-based multi-objective design optimization was performed to reduce concussion risk during frontal football helmet impacts. In particular, a topological decomposition of the football helmet facemask was performed to formulate the design problem, and brain injury metrics were exploited as objective functions. A validated finite element model of a helmeted human head was used to recreate facemask impacts. Due to the prohibitive computational expense of the full scale simulations, a surrogate modeling approach was employed. An optimal surrogate model selection framework, called Concurrent Surrogate Model Selection, or COSMOS, was utilized to identify the surrogate models best suited to approximate each objective function. The resulting surrogate models were implemented in the Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization algorithm. Constraints were implemented to control the solid material fraction in the facemask design space, and binary variables were used to control the placement of the facemask bars. The optimized facemask designs reduced the maximum tensile pressure in the brain by 7.5% and the maximum shear strain by a remarkable 39.5%. This research represents a first-of-its-kind approach to multi-objective design optimization on a football helmet, and demonstrates the possibilities that are achievable in improving human safety by using such a simulation-based design optimization. © 2016 Elsevier Ltd},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Patton, D A; McIntosh, A S; Kleiven, S
In: Journal of Applied Biomechanics, vol. 31, no. 4, pp. 264–268, 2015.
@article{Patton2015,
title = {The biomechanical determinants of concussion: Finite element simulations to investigate tissue-level predictors of injury during sporting impacts to the unprotected head},
author = {Patton, D A and McIntosh, A S and Kleiven, S},
doi = {10.1123/jab.2014-0223},
year = {2015},
date = {2015-01-01},
journal = {Journal of Applied Biomechanics},
volume = {31},
number = {4},
pages = {264--268},
abstract = {Biomechanical studies of concussions have progressed from qualitative observations of head impacts to physical and numerical reconstructions, direct impact measurements, and finite element analyses. Supplementary to a previous study, which investigated maximum principal strain, the current study used a detailed finite element head model to simulate unhelmeted concussion and no-injury head impacts and evaluate the effectiveness of various tissue-level brain injury predictors: strain rate, product of strain and strain rate, cumulative strain damage measure, von Mises stress, and intracranial pressure. Von Mises stress was found to be the most effective predictor of concussion. It was also found that the thalamus and corpus callosum were brain regions with strong associations with concussion. Tentative tolerance limits for tissue-level predictors were proposed in an attempt to broaden the understanding of unhelmeted concussions. For the thalamus, tolerance limits were proposed for a 50% likelihood of concussion: 2.24 kPa, 24.0 s-1, and 2.49 s-1 for von Mises stress, strain rate, and the product of strain and strain rate, respectively. For the corpus callosum, tolerance limits were proposed for a 50% likelihood of concussion: 3.51 kPa, 25.1 s-1, and 2.76 s-1 for von Mises stress, strain rate, and the product of strain and strain rate, respectively. © 2015 Human Kinetics, Inc.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Aomura, S; Zhang, Y; Nakadate, H; Koyama, T; Nishimura, A
Brain injury risk estimation of collegiate football player based on game video of concussion suspected accident Journal Article
In: Journal of Biomechanical Science and Engineering, vol. 11, no. 4, 2016.
Abstract | Links | BibTeX | Tags: Accidents, Brain Injury, Brain injury risk estimation, Collision accidents, DIAGNOSIS, FEM, Finite element method, FOOTBALL players, Game video, Game videos, Health risks, Initial conditions, Mechanical parameters, Motion analysis, Relative positions, RISK assessment, Risk perception, Rotational velocity, Sports, Sports-related concussion
@article{Aomura2016,
title = {Brain injury risk estimation of collegiate football player based on game video of concussion suspected accident},
author = {Aomura, S and Zhang, Y and Nakadate, H and Koyama, T and Nishimura, A},
doi = {10.1299/jbse.16-00393},
year = {2016},
date = {2016-01-01},
journal = {Journal of Biomechanical Science and Engineering},
volume = {11},
number = {4},
abstract = {The collision accident in collegiate football game was simulated based on the game video and the concussive impact on the head was analyzed. First, the collision motion of players was reproduced based on the video by using motion analysis, and the translational and rotational velocities, relative position and contact location of the struck and the striking players' heads just before the collision were calculated. Then the data obtained were input to two helmeted finite element (FE) human head models as the initial condition, and the brain injury risk was evaluated by using the impact analysis. The FE helmet model was validated by a drop test of the helmet in which the head impactor was embedded. In the present study, two concussion suspected accident cases were analyzed; then the concussion was evaluated by ten mechanical parameters generated inside the skull caused by the collision. The injury risk evaluated by multi parameters belonged to the dangerous range that may cause concussion and was consistent with the diagnosis of the medical team doctor. The brain injury risk can be successfully estimated by the reconstructed simulation of the game video and FE analysis. To our knowledge, this study is the first attempt in Japan to estimate the brain injury risk systematically by a combination of game video analysis which is originally introduced for the players' health care and FE analysis by helmeted human head model. In the future, brain injury risk caused by an accident can be evaluated with higher accuracy by analyzing more accident cases. © 2016 The Japan Society of Mechanical Engineers.},
keywords = {Accidents, Brain Injury, Brain injury risk estimation, Collision accidents, DIAGNOSIS, FEM, Finite element method, FOOTBALL players, Game video, Game videos, Health risks, Initial conditions, Mechanical parameters, Motion analysis, Relative positions, RISK assessment, Risk perception, Rotational velocity, Sports, Sports-related concussion},
pubstate = {published},
tppubtype = {article}
}
Johnson, K L; Chowdhury, S; Lawrimore, W B; Mao, Y; Mehmani, A; Prabhu, R; Rush, G A; Horstemeyer, M F
Constrained topological optimization of a football helmet facemask based on brain response Journal Article
In: Materials and Design, vol. 111, pp. 108–118, 2016.
Abstract | Links | BibTeX | Tags: Accident prevention, ALGORITHMS, brain, Concussion, Constrained optimization, Design, Design optimization, finite element analysis, Finite element method, football helmet, Fuel additives, Genetic algorithms, Multiobjective optimization, Optimization, Safety devices, Shear strain, Sports, Surrogate model, Surrogate modeling, Topology, Traumatic Brain Injuries, traumatic brain injury
@article{Johnson2016a,
title = {Constrained topological optimization of a football helmet facemask based on brain response},
author = {Johnson, K L and Chowdhury, S and Lawrimore, W B and Mao, Y and Mehmani, A and Prabhu, R and Rush, G A and Horstemeyer, M F},
doi = {10.1016/j.matdes.2016.08.064},
year = {2016},
date = {2016-01-01},
journal = {Materials and Design},
volume = {111},
pages = {108--118},
abstract = {Surrogate model-based multi-objective design optimization was performed to reduce concussion risk during frontal football helmet impacts. In particular, a topological decomposition of the football helmet facemask was performed to formulate the design problem, and brain injury metrics were exploited as objective functions. A validated finite element model of a helmeted human head was used to recreate facemask impacts. Due to the prohibitive computational expense of the full scale simulations, a surrogate modeling approach was employed. An optimal surrogate model selection framework, called Concurrent Surrogate Model Selection, or COSMOS, was utilized to identify the surrogate models best suited to approximate each objective function. The resulting surrogate models were implemented in the Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization algorithm. Constraints were implemented to control the solid material fraction in the facemask design space, and binary variables were used to control the placement of the facemask bars. The optimized facemask designs reduced the maximum tensile pressure in the brain by 7.5% and the maximum shear strain by a remarkable 39.5%. This research represents a first-of-its-kind approach to multi-objective design optimization on a football helmet, and demonstrates the possibilities that are achievable in improving human safety by using such a simulation-based design optimization. © 2016 Elsevier Ltd},
keywords = {Accident prevention, ALGORITHMS, brain, Concussion, Constrained optimization, Design, Design optimization, finite element analysis, Finite element method, football helmet, Fuel additives, Genetic algorithms, Multiobjective optimization, Optimization, Safety devices, Shear strain, Sports, Surrogate model, Surrogate modeling, Topology, Traumatic Brain Injuries, traumatic brain injury},
pubstate = {published},
tppubtype = {article}
}
Patton, D A; McIntosh, A S; Kleiven, S
In: Journal of Applied Biomechanics, vol. 31, no. 4, pp. 264–268, 2015.
Abstract | Links | BibTeX | Tags: Article, Biomechanics, brain, Brain Injury, brain region, clinical article, Concussion, corpus callosum, Damage detection, evaluation study, finite element analysis, Finite element head models, Finite element method, Finite element simulations, football, gray matter, Head Injuries, head injury, human, Intra-cranial pressure, intracranial pressure, investigative procedures, Maximum principal strain, mesencephalon, Modeling, Models, Numerical reconstruction, Qualitative observations, Sport, sport injury, Sports, Strain and strain rates, Strain rate, Stress, thalamus, Tissue, tissue level
@article{Patton2015,
title = {The biomechanical determinants of concussion: Finite element simulations to investigate tissue-level predictors of injury during sporting impacts to the unprotected head},
author = {Patton, D A and McIntosh, A S and Kleiven, S},
doi = {10.1123/jab.2014-0223},
year = {2015},
date = {2015-01-01},
journal = {Journal of Applied Biomechanics},
volume = {31},
number = {4},
pages = {264--268},
abstract = {Biomechanical studies of concussions have progressed from qualitative observations of head impacts to physical and numerical reconstructions, direct impact measurements, and finite element analyses. Supplementary to a previous study, which investigated maximum principal strain, the current study used a detailed finite element head model to simulate unhelmeted concussion and no-injury head impacts and evaluate the effectiveness of various tissue-level brain injury predictors: strain rate, product of strain and strain rate, cumulative strain damage measure, von Mises stress, and intracranial pressure. Von Mises stress was found to be the most effective predictor of concussion. It was also found that the thalamus and corpus callosum were brain regions with strong associations with concussion. Tentative tolerance limits for tissue-level predictors were proposed in an attempt to broaden the understanding of unhelmeted concussions. For the thalamus, tolerance limits were proposed for a 50% likelihood of concussion: 2.24 kPa, 24.0 s-1, and 2.49 s-1 for von Mises stress, strain rate, and the product of strain and strain rate, respectively. For the corpus callosum, tolerance limits were proposed for a 50% likelihood of concussion: 3.51 kPa, 25.1 s-1, and 2.76 s-1 for von Mises stress, strain rate, and the product of strain and strain rate, respectively. © 2015 Human Kinetics, Inc.},
keywords = {Article, Biomechanics, brain, Brain Injury, brain region, clinical article, Concussion, corpus callosum, Damage detection, evaluation study, finite element analysis, Finite element head models, Finite element method, Finite element simulations, football, gray matter, Head Injuries, head injury, human, Intra-cranial pressure, intracranial pressure, investigative procedures, Maximum principal strain, mesencephalon, Modeling, Models, Numerical reconstruction, Qualitative observations, Sport, sport injury, Sports, Strain and strain rates, Strain rate, Stress, thalamus, Tissue, tissue level},
pubstate = {published},
tppubtype = {article}
}