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}
}
Herman, D C; Barth, J T
Drop-jump landing varies with baseline neurocognition: Implications for anterior cruciate ligament injury risk and prevention Journal Article
In: American Journal of Sports Medicine, vol. 44, no. 9, pp. 2347–2353, 2016.
Abstract | Links | BibTeX | Tags: ACL, Biomechanics, Injury prevention, Motion analysis
@article{Herman2016,
title = {Drop-jump landing varies with baseline neurocognition: Implications for anterior cruciate ligament injury risk and prevention},
author = {Herman, D C and Barth, J T},
doi = {10.1177/0363546516657338},
year = {2016},
date = {2016-01-01},
journal = {American Journal of Sports Medicine},
volume = {44},
number = {9},
pages = {2347--2353},
abstract = {Background: Neurocognitive status may be a risk factor for anterior cruciate ligament (ACL) injury. Neurocognitive domains such as visual attention, processing speed/reaction time, and dual-tasking may influence ACL injury risk via alterations to neuromuscular performance during athletic tasks. However, the relationship between neurocognition and performance during athletic tasks is not yet established. Hypothesis: Athletes with low baseline neurocognitive scores will demonstrate poorer jump landing performance compared with athletes with high baseline neurocognitive score. Study Design: Controlled laboratory study. Methods: Neurocognitive performance was measured using the Concussion Resolution Index (CRI). Three-dimensional kinematic and kinetic data of the dominant limb were collected for 37 recreational athletes while performing an unanticipated jump-landing task. Healthy, nonconcussed subjects were screened using a computer-based neurocognitive test into a high performers (HP; n = 20; average CRI percentile, 78th) and a low performers (LP; n = 17; average CRI percentile, 41st) group. The task consisted of a forward jump onto a force plate with an immediate rebound to a second target that was assigned 250 milliseconds before landing on the force plate. Kinematic and kinetic data were obtained during the first jump landing. Results: The LP group demonstrated significantly altered neuromuscular performance during the landing phase while completing the jump-landing task, including significantly increased peak vertical ground-reaction force (mean ± SD of LP vs HP: 1.81 ± 0.53 vs 1.38 ± 0.37 body weight [BW]; P \<.01), peak anterior tibial shear force (0.91 ± 0.17 vs 0.72 ± 0.22 BW; P \<.01), knee abduction moment (0.47 ± 0.56 vs 0.03 ± 0.64 BW × body height; P =.03), and knee abduction angle (6.1° ± 4.7° vs 1.3° ± 5.6°; P =.03), as well as decreased trunk flexion angle (9.6° ± 9.6° vs 16.4° ± 11.2°; P \<.01). Conclusion: Healthy athletes with lower baseline neurocognitive performance generate knee kinematic and kinetic patterns that are linked to ACL injury. Clinical Relevance: Neurocognitive testing using the CRI may be useful for identification of athletes at elevated risk for future ACL injury. © American Orthopaedic Society for Sports Medicine.},
keywords = {ACL, Biomechanics, Injury prevention, Motion analysis},
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}
}
Herman, D C; Barth, J T
Drop-jump landing varies with baseline neurocognition: Implications for anterior cruciate ligament injury risk and prevention Journal Article
In: American Journal of Sports Medicine, vol. 44, no. 9, pp. 2347–2353, 2016.
@article{Herman2016,
title = {Drop-jump landing varies with baseline neurocognition: Implications for anterior cruciate ligament injury risk and prevention},
author = {Herman, D C and Barth, J T},
doi = {10.1177/0363546516657338},
year = {2016},
date = {2016-01-01},
journal = {American Journal of Sports Medicine},
volume = {44},
number = {9},
pages = {2347--2353},
abstract = {Background: Neurocognitive status may be a risk factor for anterior cruciate ligament (ACL) injury. Neurocognitive domains such as visual attention, processing speed/reaction time, and dual-tasking may influence ACL injury risk via alterations to neuromuscular performance during athletic tasks. However, the relationship between neurocognition and performance during athletic tasks is not yet established. Hypothesis: Athletes with low baseline neurocognitive scores will demonstrate poorer jump landing performance compared with athletes with high baseline neurocognitive score. Study Design: Controlled laboratory study. Methods: Neurocognitive performance was measured using the Concussion Resolution Index (CRI). Three-dimensional kinematic and kinetic data of the dominant limb were collected for 37 recreational athletes while performing an unanticipated jump-landing task. Healthy, nonconcussed subjects were screened using a computer-based neurocognitive test into a high performers (HP; n = 20; average CRI percentile, 78th) and a low performers (LP; n = 17; average CRI percentile, 41st) group. The task consisted of a forward jump onto a force plate with an immediate rebound to a second target that was assigned 250 milliseconds before landing on the force plate. Kinematic and kinetic data were obtained during the first jump landing. Results: The LP group demonstrated significantly altered neuromuscular performance during the landing phase while completing the jump-landing task, including significantly increased peak vertical ground-reaction force (mean ± SD of LP vs HP: 1.81 ± 0.53 vs 1.38 ± 0.37 body weight [BW]; P \<.01), peak anterior tibial shear force (0.91 ± 0.17 vs 0.72 ± 0.22 BW; P \<.01), knee abduction moment (0.47 ± 0.56 vs 0.03 ± 0.64 BW × body height; P =.03), and knee abduction angle (6.1° ± 4.7° vs 1.3° ± 5.6°; P =.03), as well as decreased trunk flexion angle (9.6° ± 9.6° vs 16.4° ± 11.2°; P \<.01). Conclusion: Healthy athletes with lower baseline neurocognitive performance generate knee kinematic and kinetic patterns that are linked to ACL injury. Clinical Relevance: Neurocognitive testing using the CRI may be useful for identification of athletes at elevated risk for future ACL injury. © American Orthopaedic Society for Sports Medicine.},
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}
}
Herman, D C; Barth, J T
Drop-jump landing varies with baseline neurocognition: Implications for anterior cruciate ligament injury risk and prevention Journal Article
In: American Journal of Sports Medicine, vol. 44, no. 9, pp. 2347–2353, 2016.
Abstract | Links | BibTeX | Tags: ACL, Biomechanics, Injury prevention, Motion analysis
@article{Herman2016,
title = {Drop-jump landing varies with baseline neurocognition: Implications for anterior cruciate ligament injury risk and prevention},
author = {Herman, D C and Barth, J T},
doi = {10.1177/0363546516657338},
year = {2016},
date = {2016-01-01},
journal = {American Journal of Sports Medicine},
volume = {44},
number = {9},
pages = {2347--2353},
abstract = {Background: Neurocognitive status may be a risk factor for anterior cruciate ligament (ACL) injury. Neurocognitive domains such as visual attention, processing speed/reaction time, and dual-tasking may influence ACL injury risk via alterations to neuromuscular performance during athletic tasks. However, the relationship between neurocognition and performance during athletic tasks is not yet established. Hypothesis: Athletes with low baseline neurocognitive scores will demonstrate poorer jump landing performance compared with athletes with high baseline neurocognitive score. Study Design: Controlled laboratory study. Methods: Neurocognitive performance was measured using the Concussion Resolution Index (CRI). Three-dimensional kinematic and kinetic data of the dominant limb were collected for 37 recreational athletes while performing an unanticipated jump-landing task. Healthy, nonconcussed subjects were screened using a computer-based neurocognitive test into a high performers (HP; n = 20; average CRI percentile, 78th) and a low performers (LP; n = 17; average CRI percentile, 41st) group. The task consisted of a forward jump onto a force plate with an immediate rebound to a second target that was assigned 250 milliseconds before landing on the force plate. Kinematic and kinetic data were obtained during the first jump landing. Results: The LP group demonstrated significantly altered neuromuscular performance during the landing phase while completing the jump-landing task, including significantly increased peak vertical ground-reaction force (mean ± SD of LP vs HP: 1.81 ± 0.53 vs 1.38 ± 0.37 body weight [BW]; P \<.01), peak anterior tibial shear force (0.91 ± 0.17 vs 0.72 ± 0.22 BW; P \<.01), knee abduction moment (0.47 ± 0.56 vs 0.03 ± 0.64 BW × body height; P =.03), and knee abduction angle (6.1° ± 4.7° vs 1.3° ± 5.6°; P =.03), as well as decreased trunk flexion angle (9.6° ± 9.6° vs 16.4° ± 11.2°; P \<.01). Conclusion: Healthy athletes with lower baseline neurocognitive performance generate knee kinematic and kinetic patterns that are linked to ACL injury. Clinical Relevance: Neurocognitive testing using the CRI may be useful for identification of athletes at elevated risk for future ACL injury. © American Orthopaedic Society for Sports Medicine.},
keywords = {ACL, Biomechanics, Injury prevention, Motion analysis},
pubstate = {published},
tppubtype = {article}
}