We aimed to determine whether artificial intelligence (AI)-assisted markerless motion
capture software is useful in the clinical medicine and rehabilitation fields. Currently, it is …

Background The deep learning-based human pose estimation methods, which can estimate
joint centers position, have achieved promising results on the publicly available human pose …

During the last decade markerless motion capture techniques have gained an increasing
interest in the biomechanics community. In the clinical field, however, the application of …

Introduction Recent advances in Artificial Intelligence (AI) and Computer Vision (CV) have
led to automated pose estimation algorithms using simple 2D videos. This has created the …

Estimating 3D joint rotations in the lower extremities accurately and reliably remains
unresolved in markerless motion capture, despite extensive studies in the past decades. The …

Background Markerless motion capture has the potential to perform movement analysis with
reduced data collection and processing time compared to marker-based methods. This …

Kinematic analysis is a useful and widespread tool used in research and clinical
biomechanics for the quantification of human movement. Common marker-based optical …

Markerless human motion capture could be a potential tool for studying body biomechanics.
Despite the extensive previous studies, the design of an accurate markerless system able to …

Markerless motion capturing has the potential to provide a low-cost and accessible
alternative to traditional marker-based systems for real-world biomechanical assessment …

Background Marker-less systems based on digital video cameras and deep learning for gait
analysis could have a deep impact in clinical routine. A recently developed system has …