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Validations and applications of markerless motion capture using OpenCap: a scoping review
Xiaochen Zhang1, Dunkai Mao1, Haonan Shang1
1School of Physical Education and Sports, Soochow University, Suzhou, Jiangsu, China.
Frontiers in Digital Health
|August 14, 2026
Summary
OpenCap, a smartphone-based markerless motion capture system, shows promising accuracy, particularly for sagittal-plane and lower-extremity movements. Further validation across diverse populations and improved tracking are recommended for broader biomechanical applications.
Area of Science:
- Biomechanics
- Computer Vision
- Motion Capture Technology
Background:
- Markerless motion capture systems, like OpenCap, are increasingly accessible via smartphones.
- OpenCap is gaining traction in biomechanics for lab, field, clinical, and sports applications.
- Evidence on OpenCap's validity, accuracy, and reliability is fragmented across different contexts.
Purpose of the Study:
- To synthesize evidence on OpenCap's concurrent validity, accuracy, and reliability.
- To assess OpenCap's applicability in clinical, sports, and field-based settings.
Main Methods:
- A scoping review was conducted following PRISMA-ScR guidelines.
- A systematic search identified 51 eligible studies, including validation and applied research.
- Studies were analyzed to evaluate OpenCap's performance and applicability.
Main Results:
- OpenCap demonstrated highest accuracy for sagittal-plane measurements.
- Lower-extremity measurements were more accurate than upper-extremity.
- Accuracy varied by population (healthy vs. clinical) and movement type (squat/walk vs. jump).
Conclusions:
- Future research should expand validation in diverse populations.
- Improving tracking robustness and integrating multimodal sensing are key.
- Large language model integration could enhance automated biomechanical assessment.