ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2024
Using markerless motion capture and musculoskeletal models: An evaluation of joint kinematics.
Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Concurrent Validity and Agreement of Viewpoint-Dependent Markerless Motion Tracking in Upper-Limb Assessment: A Validation Against Optoelectronic Motion Capture.Sensors (Basel, Switzerland) · 2026Article
- IMU- and Vision-Based Measurement Techniques for Joint Kinematics: A Narrative Review.Sensors (Basel, Switzerland) · 2026Review
- Optimizing camera placement in multi-view markerless motion capture: a validation study against gold-standard kinematics for static and dynamic tasks.BMC research notes · 2026Article
- Comparing kinematic and kinetic demands on the knee joint during selected physiotherapy exercises and activities of daily living.Technology and health care : official journal of the European Society for Engineering and Medicine · 2026Article
- The influence of the marker set on inverse kinematics results to inform markerless motion capture annotations.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study presents a comprehensive comparison between a marker-based motion capture system (MMC) and a video-based motion capture system (VMC) in the context of kinematic analysis using musculoskeletal models.
objectiveFocusing on joint angles, the study aimed to evaluate the accuracy of VMC as a viable alternative for biomechanical research.
methodsEighteen healthy subjects performed isolated movements with 17 joint degrees of freedom, and their kinematic data were collected using both an MMC and a VMC setup. The kinematic data were entered into the AnyBody Modelling System, which enables the calculation of joint angles. The mean absolute error (MAE) was calculated to quantify the deviations between the two systems.
resultsThe results showed good agreement between VMC and MMC at several joint angles. In particular, the shoulder, hip and knee joints showed small deviations in kinematics with MAE values of 4.8∘, 6.8∘ and 3.5∘, respectively. However, the study revealed problems in tracking hand and elbow movements, resulting in higher MAE values of 13.7∘ and 27.7∘. Deviations were also higher for head and thoracic movements.
conclusionOverall, VMC showed promising results for lower body and shoulder kinematics. However, the tracking of the wrist and pelvis still needs to be refined. The research results provide a basis for further investigations that promote the fusion of VMC and musculoskeletal models.
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