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Markerless Motion Capture for Human Movement Estimation Using Artificial Intelligence: A Systematic Review
Georgina Domènech-Garcia1,2, Xavier Marimon3,4, Andoni Carrasco-Urribarren1
1Department of Physiotherapy, Universitat Internacional de Catalunya (UIC), 08195 Barcelona, Spain.
Pediatric Reports
|July 24, 2026
Summary
AI-driven markerless motion capture (MMC) offers a promising, non-invasive approach for assessing movement disorders in children. This technology enhances pediatric healthcare by providing objective and accessible tools for diagnosis and rehabilitation.
Area of Science:
- Pediatric Healthcare Technology
- Movement Analysis
- Artificial Intelligence in Medicine
Background:
- Markerless motion capture (MMC) using artificial intelligence (AI) is transforming pediatric healthcare for movement disorder assessment.
- Video-based, sensor-free systems allow for naturalistic motion analysis in children, especially those with neurological or developmental conditions.
Purpose of the Study:
- To systematically review the clinical applicability of AI-based MMC tools in pediatric settings.
- To evaluate their use in diagnosis, motor development monitoring, and rehabilitation.
Main Methods:
- Systematic literature review (2018-2025) registered on PROSPERO (CRD42024511787).
- Inclusion of studies on pediatric populations or clinically relevant pediatric applications of MMC.
- Independent review by two specialists, with a third resolving disagreements.
Main Results:
- 52 studies selected from 1521, covering a wide age range with a focus on infant motor patterns.
- OpenPose, AlphaPose, and DeepLabCut were common AI frameworks; Theia3D showed clinical potential.
- Kinematic parameters were primary objective markers, but methodological heterogeneity and limited pediatric validation were noted.
Conclusions:
- AI-driven MMC technologies demonstrate significant potential for objective, accessible, and child-friendly movement assessment in pediatric clinical practice.
- Further validation and standardization are needed to fully integrate these tools into routine care.
