Proceedings of the Annual Conference of Biomedical Fuzzy Systems Association
Online ISSN : 2424-2586
Print ISSN : 1345-1510
ISSN-L : 1345-1510
32
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Shape Analysis of Humeral Head Shape Using Principal Component Analysis
Yuki KUBOManabu NIITomoyuki MUTOHiroshi TANAKAHiroaki IUNINaomi YAGIKatsuya NOBUHARASyoji KOBASHI
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Pages B2-2-

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Abstract

Currently, artificial humeral head is designed primarily by scaling the average shape of anatomical data. It causes a problem that the range of motion (ROM) of the shoulder is limited with the artificial shoulder joint. Improvement of similarity of artificial shoulder joint with actual one may increase the ROM. For the purpose, we previously proposed a method for constructing a statistical shape model (SSM) of the humeral head that represents the inter-individual variation of the humeral head shape using principal component analysis (PCA). In this study, we propose a method to quantitatively evaluate inter-individual variation of humeral head shape by means of shape analysis on the statistical model of humeral head. Firstly, shape analysis is applied to the constructed SSM in order to evaluate inter-individual variation of the humeral head. Next, we evaluate the reproducibility of individual artificial shoulder by the SSM. The experimental results showed that it was possible to grasp the shape characteristics of the group of subjects, and it was possible to find new shape features that were not obtained by the conventional studies with measurement of the subject shape.

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© 2019 Biomedical Fuzzy Systems Association
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