Related papers: Real-time, accurate, and open source upper-limb mu…

Marker-based Optical Motion Capture (OMC) paired with biomechanical modeling is currently considered the most precise and accurate method for measuring human movement kinematics. However, combining differentiable biomechanical modeling with…

This paper presents a biomechanically interpretable framework for gait analysis using 3D human reconstruction from video data. Unlike conventional keypoint based approaches, the proposed method extracts biomechanically meaningful markers…

Accurate 3D kinematics estimation of human body is crucial in various applications for human health and mobility, such as rehabilitation, injury prevention, and diagnosis, as it helps to understand the biomechanical loading experienced…

Tracking and reconstructing the 3D pose and geometry of two hands in interaction is a challenging problem that has a high relevance for several human-computer interaction applications, including AR/VR, robotics, or sign language…

With the increasing awareness of high-quality life, there is a growing need for health monitoring devices running robust algorithms in home environment. Health monitoring technologies enable real-time analysis of users' health status,…

Markerless estimation of 3D Kinematics has the great potential to clinically diagnose and monitor movement disorders without referrals to expensive motion capture labs; however, current approaches are limited by performing multiple…

Single-image human mesh recovery provides a compact 3D, person-centric representation that supports analysis, animation, AR and VR, rehabilitation, and human-computer interaction. However, prevailing systems impose an intact-limb prior and…

The use of motion capture has increased from last decade in a varied spectrum of applications like film special effects, controlling games and robots, rehabilitation system, animations etc. The current human motion capture techniques use…

Timely and adequate rehabilitation is critical in facilitating post-stroke recovery. However, the organization and delivery of rehabilitation are resource-demanding, and are only available to approximately 25% of stroke survivors in…

Despite significant progress in 3D human mesh estimation from RGB images; RGBD cameras, offering additional depth data, remain underutilized. In this paper, we present a method for accurate 3D human mesh estimation from a single RGBD view,…

BACKGROUND AND OBJECTIVE: Patient positioning is a crucial step in radiation therapy, for which non-invasive methods have been developed based on surface reconstruction using optical 3D imaging. However, most solutions need expensive…

Robotic ultrasound (US) imaging has been seen as a promising solution to overcome the limitations of free-hand US examinations, i.e., inter-operator variability. However, the fact that robotic US systems cannot react to subject movements…

We propose a real-time 3D human pose estimation and motion analysis method termed RePose for rehabilitation training. It is capable of real-time monitoring and evaluation of patients'motion during rehabilitation, providing immediate…

This paper presents a novel framework for real-time human action recognition in industrial contexts, using standard 2D cameras. We introduce a complete pipeline for robust and real-time estimation of human joint kinematics, input to a…

Human motion capture is frequently used to study rehabilitation and clinical problems, as well as to provide realistic animation for the entertainment industry. IMU-based systems, as well as Marker-based motion tracking systems, are the…

Walking is a key movement of interest in biomechanics, yet gold-standard data collection methods are time- and cost-expensive. This paper presents a real-time, multimodal, high sample rate lower-limb motion capture framework, based on…

This study presents an innovative computer vision framework designed to analyze human movements in industrial settings, aiming to enhance biomechanical analysis by integrating seamlessly with existing software. Through a combination of…

Exercise-based rehabilitation programs have been shown to enhance quality of life and reduce mortality and rehospitalizations. AI-driven virtual rehabilitation programs enable patients to complete exercises independently at home while AI…

We present the first real-time method to capture the full global 3D skeletal pose of a human in a stable, temporally consistent manner using a single RGB camera. Our method combines a new convolutional neural network (CNN) based pose…

Despite their potential, markerless hand tracking technologies are not yet applied in practice to the diagnosis or monitoring of the activity in inflammatory musculoskeletal diseases. One reason is that the focus of most methods lies in the…