Proceedings of the National Academy of Sciences of the United States of America
Sep 16, 2019
The integration of muscle cells with soft robotics in recent years has led to the development of biohybrid machines capable of untethered locomotion. A major frontier that currently remains unexplored is neuronal actuation and control of such muscle-...
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to th...
In a lower extremity musculoskeletal leg, the actuation kinematics define the interaction of the actuators with each other and the environment. Design of such a kinematic chain is challenging due to the existence of the redundant biarticular actuator...
Computer methods and programs in biomedicine
Sep 3, 2019
BACKGROUND AND OBJECTIVE: Rotator cuff muscle tear is one of the most frequent reason of operations in orthopedic surgery. There are several clinical indicators such as Goutallier grade and occupation ratio in the diagnosis and surgery of these disea...
The centralization of locomotor control from weak and local coupling to strong and global is hard to assess outside of particular modeling frameworks. We developed an empirical, model-free measure of centralization that compares information between c...
OBJECTIVE: To develop a deep convolutional neural network (CNN) to automatically segment an axial CT image of the pelvis for body composition measures. We hypothesized that a deep CNN approach would achieve high accuracy when compared to manual segme...
Journal of visualized experiments : JoVE
Jul 1, 2019
Mapping the motor cortex with transcranial magnetic stimulation (TMS) has potential to interrogate motor cortex physiology and plasticity but carries unique challenges in children. Similarly, transcranial direct current stimulation (tDCS) can improve...
IEEE transactions on biomedical circuits and systems
Jun 27, 2019
An accurate description of muscular activity plays an important role in the clinical diagnosis and rehabilitation research. The electromyography (EMG) is the most used technique to make accurate descriptions of muscular activity. The EMG is associate...
Automatic skeletal muscle image segmentation (MIS) is crucial in the diagnosis of muscle-related diseases. However, accurate methods often suffer from expensive computations, which are not scalable to large-scale, whole-slide muscle images. In this p...
Muscle fat infiltration (MFI) of the deep cervical spine extensors has been observed in cervical spine conditions using time-consuming and rater-dependent manual techniques. Deep learning convolutional neural network (CNN) models have demonstrated st...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.