Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics.

ABSTRACT:

Background

Traumatic brain injury can be caused by head impacts, but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo, and the characteristics of different types of impacts are not well studied. We investigated the spectral characteristics of different head impact types with kinematics classification.

Methods

Data were analyzed from 3262 head impacts from lab reconstruction, American football, mixed martial arts, and publicly available car crash data. A random forest classifier with spectral densities of linear acceleration and angular velocity was built to classify head impact types (e.g., football, car crash, mixed martial arts). To test the classifier robustness, another 271 lab-reconstructed impacts

SUBMITTER: Zhan X 

PROVIDER: S-EPMC10466194 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature