Journal
PEERJ
Volume 3, Issue -, Pages -Publisher
PEERJ INC
DOI: 10.7717/peerj.831
Keywords
Body segment parameters; Photogrammetry; Structure from motion; Subject-specific estimation; Geometric modelling; Biomechanics
Categories
Funding
- BBSRC [BB/K006029/1]
- BBSRC [BB/K006029/1] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/K006029/1] Funding Source: researchfish
Ask authors/readers for more resources
Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available