Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports.

Brain biomechanics Concussion Finite element model Impact kinematics Instrumentation Subconcussion

Journal

Annals of biomedical engineering
ISSN: 1573-9686
Titre abrégé: Ann Biomed Eng
Pays: United States
ID NLM: 0361512

Informations de publication

Date de publication:
Nov 2022
Historique:
received: 06 05 2022
accepted: 22 06 2022
pubmed: 23 7 2022
medline: 16 11 2022
entrez: 22 7 2022
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 35867314
doi: 10.1007/s10439-022-02999-w
pii: 10.1007/s10439-022-02999-w
pmc: PMC9652195
doi:

Types de publication

Review Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1389-1408

Subventions

Organisme : NINDS NIH HHS
ID : R01 NS082453
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS094410
Pays : United States

Informations de copyright

© 2022. The Author(s).

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Auteurs

Songbai Ji (S)

Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA. sji@wpi.edu.

Mazdak Ghajari (M)

Dyson School of Design Engineering, Imperial College London, London, UK.

Haojie Mao (H)

Department of Mechanical and Materials Engineering, Faculty of Engineering, Western University, London, ON, N6A 5B9, Canada.

Reuben H Kraft (RH)

Department of Mechanical and Nuclear Engineering, Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA.

Marzieh Hajiaghamemar (M)

Department of Biomedical Engineering, The University of Texas at San Antonio, San Antonio, TX, USA.

Matthew B Panzer (MB)

Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA.

Remy Willinger (R)

University of Strasbourg, IMFS-CNRS, 2 rue Boussingault, 67000, Strasbourg, France.

Michael D Gilchrist (MD)

School of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin 4, Ireland.

Svein Kleiven (S)

Division of Neuronic Engineering, KTH Royal Institute of Technology, Hälsovägen 11C, 141 57, Huddinge, Sweden.

Joel D Stitzel (JD)

Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC, USA. jstitzel@wakehealth.edu.

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