Description
- Abstract:
- Mild Traumatic Brain Injuries (mTBI) resulting from mechanical trauma remain a significant global public health concern. These injuries are often triggered by violent head motions or impacts. There is considerable interest in advancing methods to predict the resulting brain tissue strains and strain rates from such head motions. Accurately estimating the brain injury risk through these predictions is critical for developing effective prevention and mitigation strategies aimed at reducing the incidence and severity of mTBI. In this dissertation, we introduce a multiscale, physics-based approach to assess the risk of brain injury, establishing a connection between mechanical loading and brain deformation at the cellular level, where injury originates. The approach is composed of the following three key steps: Step-1: Estimate the kinematics of the individual’s head, including acceleration, angular velocity, and angular acceleration, using inertial measurement units in conjunction with motion prediction algorithms. We present an algorithm for determining the complete motion of the head using data from only four head mounted tri-axial accelerometers. The algorithm provides the rigid body’s acceleration field in both the body frame and the lab frame. Compared to other accelerometer-only algorithms, the presented algorithm is significantly less sensitive to bias type errors, such as those that arise from inaccurate measurement of sensor positions and orientations; Step-2: Estimate the strains and stain rates by inputting the kinematics and biometric information of the head into a computational continuum-mechanics-based model of the individual’s brain tissues. In this dissertation, we introduce two new idealized continuum- mechanics-based head models for predicting brain tissue strains and strain rates. One model assumes the brain behaves as an elastic material, while the other accounts for viscoelastic properties of brain tissue. Both models account for the head’s finite rotation, which is an improvement upon prior models that relied on the assumption of small rotations. Despite the simplicity of the models, we show that the proposed 2D finite rotation head models predict comparable strains to a more detailed finite element head model; Step-3: Determine the risk of injury by comparing the estimated strains with their critical values. We present a centrifugation based in vitro mTBI model that we developed in collaboration with Prof. Diane Hoffman-Kim’s group. This model can be used to estimate the critical strains.
- Notes:
- Thesis (Ph. D.)--Brown University, 2024
Citation
Wan, Yang,
"Identifying potential mild traumatic brain injury events through inertial sensor based kinematics and continuum mechanics based strain calculations"
(2024).
Mechanics of Solids Theses and Dissertations.
Brown Digital Repository. Brown University Library.
https://repository.library.brown.edu/studio/item/bdr:uvnpcjef/
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Mechanics of Solids Theses and Dissertations
Theses and Dissertations for the Mechanics of Solids department....