AIMC Topic: Biomechanical Phenomena

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Introduction to a Twin Dual-Axis Robotic Platform for Studies of Lower Limb Biomechanics.

IEEE journal of translational engineering in health and medicine
This paper presents a twin dual-axis robotic platform system which is designed for the characterization of postural balance under various environmental conditions and quantification of bilateral ankle mechanics in 2 degrees-of-freedom (DOF) during st...

FAST skill assessment from kinematics data using convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: FAST is a point of care ultrasound study that evaluates for the presence of free fluid, typically hemoperitoneum in trauma patients. FAST is an essential skill for Emergency Physicians. Thus, it requires objective evaluation tools that can r...

Hierarchical Optimization for Control of Robotic Knee Prostheses Toward Improved Symmetry of Propulsive Impulse.

IEEE transactions on bio-medical engineering
Automatically personalizing complex control of robotic prostheses to improve gait performance, such as gait symmetry, is challenging. Recently, human-in-the-loop (HIL) optimization and reinforcement learning (RL) have shown promise in achieving optim...

Jumping over fences: why field- and laboratory-based biomechanical studies can and should learn from each other.

The Journal of experimental biology
Locomotor biomechanics faces a core trade-off between laboratory-based and field-based studies. Laboratory conditions offer control over confounding factors, repeatability, and reduced technological challenges, but limit the diversity of animals and ...

Chasing the cheetah: how field biomechanics has evolved to keep up with the fastest land animal.

The Journal of experimental biology
Studying the motion of cheetahs - especially in the wild - is a technically challenging endeavour that pushes the limits of field biomechanics methodology. Consequently, it provides an interesting example of the scientific symbiosis that exists betwe...

Rethinking causality-driven robot tool segmentation with temporal constraints.

International journal of computer assisted radiology and surgery
PURPOSE: Vision-based robot tool segmentation plays a fundamental role in surgical robots perception and downstream tasks. CaRTS, based on a complementary causal model, has shown promising performance in unseen counterfactual surgical environments in...

Three-Dimensional Human Pose Estimation from Sparse IMUs through Temporal Encoder and Regression Decoder.

Sensors (Basel, Switzerland)
Three-dimensional (3D) pose estimation has been widely used in many three-dimensional human motion analysis applications, where inertia-based path estimation is gradually being adopted. Systems based on commercial inertial measurement units (IMUs) us...

A Deep Learning Model for 3D Ground Reaction Force Estimation Using Shoes with Three Uniaxial Load Cells.

Sensors (Basel, Switzerland)
Ground reaction force (GRF) is essential for estimating muscle strength and joint torque in inverse dynamic analysis. Typically, it is measured using a force plate. However, force plates have spatial limitations, and studies of gaits involve numerous...

A Concurrent Framework for Constrained Inverse Kinematics of Minimally Invasive Surgical Robots.

Sensors (Basel, Switzerland)
Minimally invasive surgery has undergone significant advancements in recent years, transforming various surgical procedures by minimizing patient trauma, postoperative pain, and recovery time. However, the use of robotic systems in minimally invasive...

Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics.

Journal of sport and health science
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 may undergo, and the characteristics of different types of impacts are...