Optical motion capture is currently the most popular method for acquiring motion data in
biomechanical applications. However, it presents a number of problems that make the …

Optical motion capture is a mature contemporary technique for the acquisition of motion
data; alas, it is non-error-free. Due to technical limitations and occlusions of markers, gaps …

Ultrasound-based Hand Gesture Recognition has gained significant attention in recent
years. While static gesture recognition has been extensively explored, only a few works …

The robotic surgery environment represents a typical scenario of human–robot cooperation.
In such a scenario, individuals, robots, and medical devices move relative to each other …

Flexible barriers are vulnerable to consecutive rockfall impacts, particularly in mountainous
areas. The barriers deformation, energy absorption, and anti-impact performance can be …

In the context of human–robot collaborative shared environments, there has been an
increase in the use of optical motion capture (OMC) systems for human motion tracking. The …

Optical motion capture systems are prone to errors connected to marker recognition (eg,
occlusion, leaving the scene, or mislabeling). These errors are then corrected in the …

In the article, we study application of tree based regression methods for reconstruction of
gaps in marker trajectories in optical motion capture systems. Having perfect ground truth …

We demonstrate a simple, low-cost, and well-performing optical phase-locked loop (OPLL)
circuit with ADF4007 as the phase frequency detector chip to achieve frequency and phase …

Accurate measurement of human joint angles during gait is crucial for understanding
movement biomechanics and assessing musculoskeletal conditions. Inertial measurement …