AI-Based Identification of Head Impact Locations, Speeds, and Force Based on Head Kinematics Simulations
The precision on simulations underscores the model's potential in enhancing helmet design and safety in sports by providing more accurate impact data. Future studies should test the models across various helmets and sports on large in vivo datasets to validate the accuracy of the models, employing techniques like transfer learning to broaden its effectiveness.
Authors
- Michael Zeineh (ORCID: https://orcid.org/0000-0002-6940-9096)
- Nicholas J. Cecchi (ORCID: https://orcid.org/0000-0001-9319-4163)
- Xianghao Zhan (ORCID: https://orcid.org/0000-0002-7058-2603)
- David B. Camarillo (ORCID: https://orcid.org/0000-0003-4965-2977)
- Olivier Gevaert (ORCID: https://orcid.org/0000-0002-9965-5466)
- Yuzhe Liu (ORCID: https://orcid.org/0000-0002-9451-0620)
- Ashlyn A. Callan (ORCID: https://orcid.org/0009-0006-7804-3563)
- Jessica Towns
Institutions
- Beihang University (CN)
- Stanford University (US)
Publication Details
- Journal
- IEEE Transactions on Biomedical Engineering
- Published
- 2025-06-19
- DOI
- https://doi.org/10.1109/tbme.2025.3581171
- Citations
- 1
- Primary Topic
- Traumatic Brain Injury Research
- Type
- article
- Field-Weighted Citation Impact
- 1.35