Classification of head impacts based on the spectral density of measurable kinematics

by   Xianghao Zhan, et al.

Traumatic brain injury can be caused by head impacts, but many brain injury risk estimation models are less accurate across the variety of impacts that patients may undergo. In this study, we investigated the spectral characteristics of different head impact types with kinematics classification. Data was analyzed from 3262 head impacts from head model simulations, on-field data from American football and mixed martial arts (MMA) using our instrumented mouthguard, and publicly available car crash data. A random forest classifier with spectral densities of linear acceleration and angular velocity was built to classify different types of head impacts (e.g., football, MMA), reaching a median accuracy of 96 Furthermore, to test the classifier on data from different measurement devices, another 271 lab-reconstructed impacts were obtained from 5 other instrumented mouthguards with the classifier reaching over 96 The most important features in classification included both low-frequency and high-frequency features, both linear acceleration features and angular velocity features. It was found that different head impact types had different distributions of spectral densities in low-frequency and high-frequency ranges (e.g., the spectral densities of MMA impacts were higher in high-frequency range than in the low-frequency range). Finally, with head impact classification, type-specific, nearest-neighbor regression models were built for 95th percentile maximum principal strain, 95th percentile maximum principal strain in corpus callosum, and cumulative strain damage (15th percentile). This showed a generally higher R^2-value than baseline models without classification.


page 5

page 7


Kinematics clustering enables head impact subtyping for better traumatic brain injury prediction

Traumatic brain injury can be caused by various types of head impacts. H...

Prediction of brain strain across head impact subtypes using 18 brain injury criteria

Multiple brain injury criteria (BIC) are developed to quickly quantify b...

Axonal Conduction Velocity Impacts Neuronal Network Oscillations

Increasing experimental evidence suggests that axonal action potential c...

Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation

Brain tissue deformation resulting from head impacts is primarily caused...

Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusion

Brain strain and strain rate are effective in predicting traumatic brain...

Data-driven decomposition of brain dynamics with principal component analysis in different types of head impacts

Strain and strain rate are effective traumatic brain injury predictors. ...

Investigating and Explaining the Frequency Bias in Image Classification

CNNs exhibit many behaviors different from humans, one of which is the c...

Please sign up or login with your details

Forgot password? Click here to reset