Validation and Comparison of Instrumented Mouthguards for Measuring Head Kinematics and Assessing Brain Deformation in Football Impacts
Not on the map. Why?
Abstract (arXiv)
Because of the relatively rigid coupling between the upper dentition and the skull, instrumented mouthguards have been shown to be a viable way of measuring head impact kinematics for assisting in understanding the underlying biomechanics of concussions. This has led various companies and institutions to further develop instrumented mouthguards. However, their use as a research tool for understanding concussive impacts makes quantification of their accuracy critical, especially given the conflicting results from various recent studies. Here we present a study that uses a pneumatic impactor to deliver impacts characteristic to football to a Hybrid III headform, in order to validate and compare five of the most commonly used instrumented mouthguards. We found that all tested mouthguards gave accurate measurements for the peak angular acceleration (mean relative error, MRE < 13%), the peak angular velocity (MRE < 8%), brain injury criteria values (MRE < 13%) and brain deformation (described as maximum principal strain and fiber strain, calculated by a convolutional neural network based brain model, MRE < 9%). Finally, we found that the accuracy of the measurement varies with the impact locations yet is not sensitive to the impact velocity for the most part.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Aug 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 5; 2022: 1; 2023: 1; 2024: 1.
8 papers.
- 2021Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretationcited by 8
- 2021Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematicscited by 3
- 2021Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusioncited by 3
- 2021Data-driven decomposition of brain dynamics with principal component analysis in different types of head impactscited by 2
- 2021Kinematics clustering enables head impact subtyping for better traumatic brain injury predictioncited by 1
- 2022Denoising instrumented mouthguard measurements of head impact kinematics with a convolutional neural networkcited by 1
- 2023Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptationcited by 0
- 2024Identification of head impact locations, speeds, and force based on head kinematicscited by 0
- 2024Identification of head impact locations, speeds, and force based on head kinematics12 Sep 2024
- 2023Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation8 Jun 2023
- 2022Denoising instrumented mouthguard measurements of head impact kinematics with a convolutional neural network19 Dec 2022
- 2021Data-driven decomposition of brain dynamics with principal component analysis in different types of head impacts27 Oct 2021
- 2021Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusion31 Aug 2021
- 2021Kinematics clustering enables head impact subtyping for better traumatic brain injury prediction7 Aug 2021
- 2021Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics19 Apr 2021
- 2021Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation9 Feb 2021