Advancing our understanding of spinal biomechanics through Finite Element Analysis (FEA) is essential for clinical decision-making and biomechanical research. Traditional FEA workflows are hindered by manual segmentation and meshing, introducing inco...
Journal of neuroengineering and rehabilitation
Oct 9, 2025
BACKGROUND: Elderly patients often face challenges in recovering from distal radius fractures (DRFs), and inadequately guided rehabilitation may lead to delayed healing or secondary injury.
Skeleton-based action recognition has emerged as a promising field within computer vision, offering structured representations of human motion. While existing Graph Convolutional Network (GCN)-based approaches primarily rely on raw 3D joint coordinat...
Computer vision and artificial intelligence (AI) have become increasingly important in behavioral analysis across biological research. In contrast to well-established methods for individual behavior analysis, computational frameworks for quantitative...
BACKGROUND: Tibial fractures are among the most common complex orthopedic injuries. The mechanical strength and biomaterial properties of implants used in the treatment of such fractures directly affect the healing process. In this study, the mechani...
The passive compliance of a soft worm-like body can be a key advantage for traversal of complex confined spaces, but in practice, the body's stiffness and contact friction often require experimental adjustments. Here, for the first time, we develop a...
Biochemical and biophysical research communications
Oct 4, 2025
The extracellular matrix (ECM) is crucial in tuning cellular behavior, and quantifying cellular mechanical changes in response to ECM stimuli can help reveal the underlying physical mechanisms of cell-ECM interactions for a comprehensive understandin...
The kinematic reliability analysis of robotic manipulators is crucial due to uncertainties such as joint variations, manufacturing tolerances, and external disturbances. Traditional methods often rely on analytical techniques that struggle with nonli...
The integration of robotics and Electrical Stimulation (ES) in neurorehabilitation leverages robotics' precise task execution alongside ES-induced motor learning, muscle conditioning, and cardiovascular benefits. We propose a hybrid system for overgr...
This study aimed to verify and interpret a model for predicting the number of home runs per year using sensor data from professional baseball players during batting practice. A machine learning model was constructed using Random Forest from the bat k...
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