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Original scientific paper

https://doi.org/10.1080/00051144.2018.1517513

3D sensing of back symmetry curve suited for dynamic analysis of spinal deformities

Matea Ðonlić ; Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
Tomislav Petković ; Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
Stanislav Peharec ; Polyclinic for Physical Medicine and Rehabilitation Peharec, Pula, Croatia
Tomislav Pribanić ; Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia


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Abstract

This paper is focused on meeting the demands for better detection and evaluation of the spinal deformities that go beyond a basic static 3D analysis. It is expected that by observing the spine while it moves an improved 3D deformity analysis and measurements can be achieved.
In this paper, we present a novel approach for the automatic back symmetry curve sensing. Our approach can be used in the back shape analysis of many different positions, i.e. segments of the dynamic motion, and is not limited only to the upright standing position. The proposed method is based on the 3D surface reconstruction, surface curvature analysis and graph theoretic approach for the (semi-)automatic detection of the symmetry curve. In addition, we introduce a 3D scanning system which was used in our experiment to successfully generate 3D back surface reconstructions for each frame of the captured forward bending motion. We also tested the proposed method on the data collected using commercial 3D spine analysis system and the results were comparable. The additional experiment focusing on the dynamic analysis demonstrated that the proposed method can enable further advances in the automatic 3D back surface analysis by tracking the spine position throughout performed movements.

Keywords

3D Back shape analysis; stereophotogrammetry; spinal deformities; surface curvature analysis; symmetry curve; forward bending motion

Hrčak ID:

225191

URI

https://hrcak.srce.hr/225191

Publication date:

28.9.2018.

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