Abstract
The present study proposed a method to estimate the finite finger joint centers of rotation (CoRs) with high accuracy using 3D hand skeleton motions reconstructed from CT scans. Ten hand postures starting from a fully extended posture and ending at a fist posture with about 10° difference in flexion between the adjacent postures were captured by a CT scanner for 15 male participants, and their 3D hand skeletons were reconstructed using the CT scans. Each bone segment from the full extension posture was registered to the corresponding bone segments of the remaining hand postures. The proximal bone segments of a joint from two postures were aligned to estimate the finite CoR of the joint between the two postures. Centerlines of the distal bone segments of the joint were then identified using the principal component analysis method, and the finite CoR of the joint was determined as the intersection point of the identified centerlines. The proposed method reduced the variation of estimated finite joint CoRs by 16.0% to 67.0% among the finger joints compared to the existing methods. The variation of estimated finite joint CoRs decreased as the rotation angle of the joint increased. The proposed method can be used for the simulation of finger movement with high accuracy.
Funder
Fundamental Research Funds for the Central Universities
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
7 articles.
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