Evidence map›Paper›PMID 35867314›Full record

ReviewAnnals of biomedical engineering2022

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

Songbai Ji, Mazdak Ghajari, Haojie Mao, Reuben H Kraft, Marzieh Hajiaghamemar, Matthew B Panzer, Remy Willinger, Michael D Gilchrist, Svein Kleiven, Joel D Stitzel

Open access · hybridAbstract readReview
In one paragraph

Review in Annals of biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
12.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 87 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Multimodal characterization of intracranial biomechanics in a 3D biofidelic head surrogate.Journal of the mechanical behavior of biomedical materials · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Quantitative video analysis of head acceleration events: a review.Frontiers in bioengineering and biotechnology · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 10 institutions in 6 countries.

Songbai JiDepartment of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA. sji@wpi.edu.ORCID http://orcid.org/0000-0002-2886-5781
Mazdak GhajariDyson School of Design Engineering, Imperial College London, London, UK.
Haojie MaoDepartment of Mechanical and Materials Engineering, Faculty of Engineering, Western University, London, ON, N6A 5B9, Canada.
Reuben H KraftDepartment of Mechanical and Nuclear Engineering, Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA.
Marzieh HajiaghamemarDepartment of Biomedical Engineering, The University of Texas at San Antonio, San Antonio, TX, USA.
Matthew B PanzerDepartment of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA.
Remy WillingerUniversity of Strasbourg, IMFS-CNRS, 2 rue Boussingault, 67000, Strasbourg, France.
Michael D GilchristSchool of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
Svein KleivenDivision of Neuronic Engineering, KTH Royal Institute of Technology, Hälsovägen 11C, 141 57, Huddinge, Sweden.
Joel D StitzelDepartment of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC, USA. jstitzel@wakehealth.edu.
Centre National de la Recherche Scientifique · FRDyson (United Kingdom) · GBKTH Royal Institute of Technology · SEPennsylvania State University · USThe University of Texas at San Antonio · USUniversity College Dublin · IEUniversity of Virginia · USWake Forest University · USWestern University · CAWorcester Polytechnic Institute · US

Funding

Biomechanical Basis of Pediatric mTBI Due to Sports Related ConcussionR01NS094410 · NINDS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI DUMA, STEFAN, GREENWALD, RICHARD M · 2015 to 2019
$3.3M
iTAKL: Imaging Telemetry And Kinematic modeLing in youth footballR01NS082453 · NINDS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI GIOIA, GERARD A., MALDJIAN, JOSEPH A · 2014 to 2018
$3.3M
NINDS NIH HHS R01 NS082453NINDS NIH HHS R01 NS094410
6 · The paper itself

Abstract

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.

Indexed as

Brain ConcussionSportsAccelerationBiomechanical PhenomenaBrainHeadHumansBrain biomechanicsConcussionFinite element modelImpact kinematicsInstrumentationSubconcussion

Identifiers

PMID35867314
PMCPMC9652195
OpenAlexW4286559721

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.