Translational models of mild traumatic brain injury tissue biomechanics
Traumatic brain injury (TBI) is a global health concern. Mild TBI (mTBI) which accounts for
the majority of TBI cases, is hard to detect since often the imaging is normal but can still …
the majority of TBI cases, is hard to detect since often the imaging is normal but can still …
Applications of AI in martial arts: A survey
Y Pang, Y Wang, Q Wang, F Li… - Proceedings of the …, 2024 - journals.sagepub.com
Artificial intelligence (AI) has become an interdisciplinary subject that integrates digital
image processing, machine learning, and computer science, etc. A lot of work in martial arts …
image processing, machine learning, and computer science, etc. A lot of work in martial arts …
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 …
Multi-scale spatio-temporal fusion with adaptive brain topology learning for fMRI based neural decoding
Z Li, Q Li, Z Zhu, Z Hu, X Wu - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
Neural decoding aims to extract information from neurons' activities to reveal how the brain
functions. Due to the inherent spatial and temporal characteristics of brain signals, spatio …
functions. Due to the inherent spatial and temporal characteristics of brain signals, spatio …
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 …
Piecewise multivariate linearity between kinematic features and cumulative strain damage measure (csdm) across different types of head impacts
In a previous study, we found that the relationship between brain strain and kinematic
features cannot be described by a generalized linear model across different types of head …
features cannot be described by a generalized linear model across different types of head …
BiGuide: A bi-level data acquisition guidance for object detection on mobile devices
Object detection (OD) is crucial for numerous emerging visual sensing applications. As OD
models trained on unrepresentative data usually yield poor performance, collecting high …
models trained on unrepresentative data usually yield poor performance, collecting high …
[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 …
AI-based denoising of head impact kinematics measurements with convolutional neural network for traumatic brain injury prediction
Objective: Wearable devices are developed to measure head impact kinematics but are
intrinsically noisy because of the imperfect interface with human bodies. This study aimed to …
intrinsically noisy because of the imperfect interface with human bodies. This study aimed to …