TY - JOUR
T1 - Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports
AU - Ji, Songbai
AU - Ghajari, Mazdak
AU - Mao, Haojie
AU - Kraft, Reuben H.
AU - Hajiaghamemar, Marzieh
AU - Panzer, Matthew B.
AU - Willinger, Remy
AU - Gilchrist, Michael D.
AU - Kleiven, Svein
AU - Stitzel, Joel D.
N1 - Funding Information:
Support for the CHAMP consensus conference was obtained from the National Football League and Football Research Inc. SJ is supported by the National Science Foundation (NSF) under Award Number 2114697. RHK is supported by the NSF under Award Number 1846059. MH is supported by the NSF under award number 2138719. JS is supported by the NIH under Awards R01NS094410 and R01NS082453. Any opinions, findings and conclusions expressed in this article are those of the authors and do not necessarily reflect the views of the National Science Foundation or the National Institutes of Health.
Funding Information:
Support for the CHAMP consensus conference was obtained from the National Football League and Football Research Inc. SJ is supported by the National Science Foundation (NSF) under Award Number 2114697. RHK is supported by the NSF under Award Number 1846059. MH is supported by the NSF under award number 2138719. JS is supported by the NIH under Awards R01NS094410 and R01NS082453. Any opinions, findings and conclusions expressed in this article are those of the authors and do not necessarily reflect the views of the National Science Foundation or the National Institutes of Health.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/11
Y1 - 2022/11
N2 - Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.
AB - Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.
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U2 - 10.1007/s10439-022-02999-w
DO - 10.1007/s10439-022-02999-w
M3 - Article
C2 - 35867314
AN - SCOPUS:85133878127
SN - 0090-6964
VL - 50
SP - 1389
EP - 1408
JO - Annals of Biomedical Engineering
JF - Annals of Biomedical Engineering
IS - 11
ER -