Robotic artificial muscles, inspired by the adaptability of biological muscles, outperform rigid robots in dynamic environments due to their flexibility. However, the intrinsic compliance of the soft actuators restricts force transmission capacity an...
Artificial neural networks (ANNs) offers potential for obtaining kinetics in non-laboratory. This study compared the estimation performance for ground reaction forces (GRF) and lower-limb joint moments during sidestepping between ANNs fed with full-b...
Acta of bioengineering and biomechanics
Jan 27, 2025
Monitoring and assessing the level of lower limb motor skills using the Biodex System plays an important role in the training of football players and in post-traumatic rehabilitation. The aim of this study was to build and test an artificial intelli...
Journal of the mechanical behavior of biomedical materials
Jan 25, 2025
Biological tissues dynamically adapt their mechanical properties at the microscale in response to stimuli, often governed by discrete interacting mechanisms that dictate the material's behavior at the macroscopic scale. An approach to model the discr...
The cable-driven hyper-redundant manipulator (CDHM), distinguished by its high flexibility and adjustable stiffness, is extensively utilized in confined and obstacle-rich environments such as aerospace and nuclear facilities. This paper introduces a ...
Flying insects have developed two distinct adaptive strategies to minimize wing damage during collisions. One strategy includes an elastic joint at the leading edge, which is evident in wasps and beetles, while another strategy features an adaptive a...
Robots have to adjust their motor behavior to changing environments and variable task requirements to successfully operate in the real world and physically interact with humans. Thus, robotics strives to enable a broad spectrum of adjustable motor be...
The KinaTrax markerless motion capture system, used extensively in the analysis of baseball pitching and hitting, is currently being adapted for use in clinical biomechanics. In clinical and laboratory environments, repeatability is inherent to the q...
We present a built-in physics neural network architecture, known as inelastic Constitutive Artificial Neural Network (iCANN), to discover the inelastic phenomenon of tensional homeostasis. In this course, identifying the optimal model and material pa...
BACKGROUND: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground Reaction Forces (GRF), providing a novel perspective on human gait analysis. This approach aims to e...