Brain deformation estimation with transfer learning for head impact datasets across impact types
Objective: The machine-learning head model (MLHM) to accelerate the calculation of brain
strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model …
strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model …
Adaptive machine learning head model across different head impact types using unsupervised domain adaptation and generative adversarial networks
Machine learning head models (MLHMs) are developed to estimate brain deformation from
sensor-based kinematics for early detection of traumatic brain injury (TBI). However, the …
sensor-based kinematics for early detection of traumatic brain injury (TBI). However, the …
Differences between two maximal principal strain rate calculation schemes in traumatic brain analysis with in-vivo and in-silico datasets
Brain deformation caused by a head impact leads to traumatic brain injury (TBI). The
maximum principal strain (MPS) was used to measure the extent of brain deformation and …
maximum principal strain (MPS) was used to measure the extent of brain deformation and …
Efficient generation of pretraining samples for developing a deep learning brain injury model via transfer learning
The large amount of training samples required to develop a deep learning brain injury
model demands enormous computational resources. Here, we study how a transformer …
model demands enormous computational resources. Here, we study how a transformer …
Assessing Head Acceleration Events in Female Community Rugby Union Players: A Cohort Study Using Instrumented Mouthguards
MD Bussey, D Salmon, B Nanai, J Romanchuk… - Sports Medicine, 2024 - Springer
Background The rapid growth of women's rugby union has underscored the need for female-
specific player welfare protocols, particularly regarding the risk of head injuries …
specific player welfare protocols, particularly regarding the risk of head injuries …
[HTML][HTML] Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics
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 …
risk estimation models are not equally accurate across the variety of impacts that patients …
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 injury (TBI) caused by
head impacts. However, state-of-the-art finite element modeling (FEM) demands …
head impacts. However, state-of-the-art finite element modeling (FEM) demands …
[PDF][PDF] 创伤性脑损伤研究的人类头部有限元模型研究进展
张艺涵， 王阳， 展祥皓， 周舟， 刘雨喆， 王丽珍， 樊瑜波 - 爆炸与冲击, 2025 - bzycj.cn
5. 斯坦福大学生物工程系, 美国加州斯坦福94305; 6. 斯坦福大学生物医学数据科学系,
美国加州斯坦福94305; 7. 瑞典皇家理工学院神经元工程部门, 瑞典斯德哥尔摩14152) 摘要 …
美国加州斯坦福94305; 7. 瑞典皇家理工学院神经元工程部门, 瑞典斯德哥尔摩14152) 摘要 …
[HTML][HTML] Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation
Abstract Machine learning head models (MLHMs) are developed to estimate brain
deformation for early detection of traumatic brain injury (TBI). However, the overfitting to …
deformation for early detection of traumatic brain injury (TBI). However, the overfitting to …
The Role of Spreading Depolarizations in Mild Traumatic Brain Injuries
NJ Pinkowski - 2024 - search.proquest.com
Mild traumatic brain injuries (mTBIs) often lead to acute symptoms like disorientation and
discoordination, but the underlying mechanisms are unknown. Although most patients …
discoordination, but the underlying mechanisms are unknown. Although most patients …