152 citations · 472 across the 20 of their papers we have counts for
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Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation
Xianghao Zhan, Jiawei Sun, Yuzhe Liu +5
Machine learning head models (MLHMs) are developed to estimate brain deformation for early detection of traumatic brain injury (TBI). However, the overfitting to simulated impacts…
Denoising instrumented mouthguard measurements of head impact kinematics with a convolutional neural network
Xianghao Zhan, Yuzhe Liu, Nicholas J. Cecchi +6
Wearable sensors for measuring head kinematics can be noisy due to imperfect interfaces with the body. Mouthguards are used to measure head kinematics during impacts in traumatic b…
Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusion
Xianghao Zhan, Yuzhe Liu, Nicholas J. Cecchi +4
Brain strain and strain rate are effective in predicting traumatic brain injury (TBI) caused by head impacts. However, state-of-the-art finite element modeling (FEM) demands consid…
A New Open-Access Platform for Measuring and Sharing mTBI Data
August G. Domel, Samuel J. Raymond, Chiara Giordano +22
Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes,…