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Markerless motion capture (mocap) could be the future of motion analysis. The purpose of this report was to describe our team of clinicians and scientists' exploration of markerless mocap (Theia 3D) and share data for others to explore (link: https://osf.io/6vh7z/?view_only=c0e00984e94a48f28c8d987a2127339d). Simultaneous mocap was performed using markerless and marker-based systems for walking, squatting, and forward hopping. Segment lengths were more variable between trials using markerless mocap compared to marker-based mocap. Sagittal plane angles were most comparable between systems at the knee joint followed by the ankle and hip. Frontal and transverse plane angles were not comparable between systems. The data collection experience using markerless mocap was simpler, faster, and user friendly. The ease of collection was in part offset by the added data transfer and processing times, and the lack of troubleshooting flexibility. If used selectively with proper understanding of limitations, markerless mocap can be exciting technology to advance the field of motion analysis.
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http://dx.doi.org/10.1016/j.jsampl.2022.100001 | DOI Listing |
J Sports Sci
August 2025
Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.
Evaluating movement quality in dynamic tasks is vital in return-to-sport (RTS) decision-making, yet marker-based motion capture (MoCap) can be complex. This study assessed the inter-session reliability of lower extremity joint kinematics and kinetics obtained using Theia3D, a markerless MoCap solution, during dynamic RTS screening tasks. Eighteen healthy participants performed six tasks over two sessions.
View Article and Find Full Text PDFSensors (Basel)
July 2025
Sport Biomechanics Lab, School of Kinesiology, Auburn University, 301 Wire Rd, Auburn, AL 36830, USA.
Motion capture (MoCap) technologies have transformed athlete monitoring, yet athletic departments face complex decisions when selecting systems for multiple sports. We conducted a narrative review of peer-reviewed studies (2015-2025) examining optical marker-based, inertial measurement unit (IMU) systems, including Global Navigation Satellite System (GNSS)-integrated systems, and markerless computer vision systems. Studies were evaluated for validated accuracy metrics across indoor court, aquatic, and outdoor field environments.
View Article and Find Full Text PDFMed Eng Phys
August 2025
Department of Rehabilitation, Hospital for Special Surgery, 535 E 70th ST, NY 10021, USA.
Background: Markerless motion capture is faster than a traditional marker-based method, but its reliability is not well established. The limitations of this new technology must be understood to ensure its appropriate utilization.
Research Question: Does a markerless motion capture system exhibit intra-device and inter-device reliability with an Intraclass Correlation Coefficient (ICC) > 0.
IEEE Int Conf Rehabil Robot
May 2025
This study investigates feature analysis and feature fusion from different sensor modalities for the task of identifying movement errors in physiotherapeutic exercises, using squats as a case study. Incorrectly performed exercises can lead to injuries, underscoring the need for accurate monitoring tools. In an experiment, ten participants performed squats in three variations: correct execution, forward lean, and lateral tilt.
View Article and Find Full Text PDFSchizophr Res
July 2025
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Centre for Mental Health (DZPG), partner site Mannheim-Heidelberg-Ulm, Mannheim, Germany. Electronic address:
Background: Three-dimensional (3D) markerless motion capture (MoCap) systems are emerging as powerful tools for the objective assessment of sensori-/psychomotor abnormalities in mental disorders. However, the application of 3D-MoCap technology for gait analysis in catatonia remains unexplored.
Methods: This study included 23 patients with and 53 patients without catatonia, classified according to ICD-11.