Format

Send to

Choose Destination
J Biomech. 2019 Mar 6;85:173-181. doi: 10.1016/j.jbiomech.2019.01.030. Epub 2019 Jan 24.

A principal component analysis-based framework for statistical modeling of bone displacement during wrist maneuvers.

Author information

1
Department of Biomedical Engineering, University of California Davis, Davis, CA 95616, USA.
2
Department of Radiology, University of California Davis School of Medicine, Sacramento, CA 95817, USA.
3
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, USA.
4
Department of Orthopedic Surgery, University of California Davis School of Medicine, Sacramento, CA 95817, USA.
5
Department of Radiology, University of California Davis School of Medicine, Sacramento, CA 95817, USA. Electronic address: ajchaudhari@ucdavis.edu.

Abstract

We present a method for the statistical modeling of the displacements of wrist bones during the performance of coordinated maneuvers, such as radial-ulnar deviation (RUD). In our approach, we decompose bone displacement via a set of basis functions, identified via principal component analysis (PCA). We utilized MRI wrist scans acquired at multiple static positions for deriving these basis functions. We then utilized these basis functions to compare the displacements undergone by the bones of the left versus right wrist in the same individual, and between bones of the wrists of men and women, during the performance of the coordinated RUD maneuver. Our results show that the complex displacements of the wrist bones during RUD can be modeled with high reliability with just 5 basis functions, that captured over 91% of variation across individuals. The basis functions were able to predict intermediate wrist bone poses with an overall high accuracy (mean error of 0.26 mm). Our proposed approach found statistically significant differences between bone displacement trajectories in women versus men, however, did not find significant differences in those of the left versus right wrist in the same individual. Our proposed method has the potential to enable detailed analysis of wrist kinematics for each sex, and provide a robust framework for characterizing the normal and pathologic displacement of the wrist bones, such as in the context of wrist instability.

KEYWORDS:

Principal component analysis; Sex differences; Statistical modeling; Wrist bone displacement

PMID:
30738587
PMCID:
PMC6434941
[Available on 2020-03-06]
DOI:
10.1016/j.jbiomech.2019.01.030

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center