Deception detection has attracted broad interest in professional practice and academic research, and body movement is considered one of the key aspects in deception detection. Previous work has focused on certain body parts (i.e., hand, head, leg) or...
This study explored the integration of markerless motion capture and deep learning to classify knee osteoarthritis severity based on gait kinematics, providing an alternative to traditional assessment methods. We employed a Long Short-Term Memory Ful...
This study reviewed the literature regarding reliability and validity of markerless motion capture (MMC) for measuring lower extremities and trunk kinematics during sports-related and functional tasks. Articles published until 28 February 2024 were a...
Markerless motion capture (ML) systems, which utilize deep learning algorithms, have significantly expanded the applications of biomechanical analysis. Jump tests are now essential tools for athlete monitoring and injury prevention. However, the vali...
The study hypothesised that a markerless motion capture system can provide kinematic data comparable to a traditional marker-based system for riders mounted on a horse. The objective was to assess the markerless system's accuracy by directly comparin...
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...
Marker-based optical motion capture systems have been used as a cardinal vehicle to probe and understand the underpinning mechanism of human posture and movement, but it is time-consuming for complex and delicate data acquisition and analysis, labor-...
Falls are a major issue for those over the age of 65 years worldwide. Objective assessment of fall risk is rare in clinical practice. The most common methods of assessment are time-consuming observational tests (clinical tests). Computer-aided diagno...
This study examined the efficacy of an optimized DeepLabCut (DLC) model in motion capture, with a particular focus on the sit-to-stand (STS) movement, which is crucial for assessing the functional capacity in elderly and postoperative patients. This ...
In recent years, researchers have focused on analyzing humans' daily living activities to study various performance metrics that humans subconsciously optimize while performing a particular task. In order to recreate these motions in robotic structur...
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