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.
Highlights
The hand is a complex interface that performs various manual tasks, such as manipulating objects, communicating, typing, and playing musical instruments
center of rotation (CoR) among different postureswere for the MCP, proximal interphalangeal (PIP), and joints of of the index, middle, little fingers of each participant estimated with the proposed the index, middle, ring, and little fingers of each participant were estimated with the proposed the index, middle, ring, and little fingers ofthe each participant estimated the proposed method and Reuleaux’s
The present study proposed a novel method to estimate finite finger joint CoRs using 3D hand skeleton motions reconstructed from computedpostures tomography (CT) scans
Summary
The hand is a complex interface that performs various manual tasks, such as manipulating objects, communicating, typing, and playing musical instruments. Digital human hand models have been widely used in ergonomic product design and evaluation [1,2,3,4,5,6,7]. Endo et al [4] developed a system for the ergonomic design and assessment of a handheld information appliance by integrating a digital hand with a product model and corresponding tasks to save development time and cost. Fixed joint CoRs can be estimated using surface marker-defined finger motions [8,9,10,11] or bone curvature-based method [12,13]. Zhang et al [11] estimated finger joint CoR locations from measured surface marker flexion-extension motions by minimizing the time-variance of the internal link lengths based on an empirically
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