This study proposes and demonstrates the design, implementation, and characterization of a 3D-printed smartpolymer sensor array using conductive polyaniline (PANI) structures embedded in a polymeric substrate. The piezoresistive characteristics of PANI were studied to evaluate the efficacy of the manufacturing of an embedded pressure sensor. PANI’s stability throughout loading and unloading cycles together with the response to incremental loading cycles was investigated. It is demonstrated that this specially developed multi-material additive manufacturing process for polyaniline is a good candidate for the manufacture of implant components with smart-polymer sensors embedded for the analysis of joint loads in orthopaedic implants.
An important aspect of implant replacement of the human joint is the fit achieved between the implant and bone canal.
As the implant is inserted within the medullary canal, its position and orientation is subjected to a variety of constraints
introduced either by the external forces and moments applied by the surgeon or by the interaction of the implant with the
cortical wall of the medullary canal. This study evaluated the implant-bone interaction of a humeral stem in elbow
replacement surgery as an example, but the principles can also be applied to other joints. After converting CT scan data
of the humerus to the parametric NURBS-based representation, a collision detection procedure based on existing
Computer-Aided Engineering techniques was employed to control the instantaneous kinematics and dynamics of the
insertion of a humeral implant in an attempt to determine its final posture within the canal. By measuring the
misalignment between the native flexion-extension (FE) axis of the distal humerus and the prosthesis, a prediction was
made regarding the fit between the canal and the implant. This technique was shown to be effective in predicting the
final misalignment of the implant axis with respect to the native FE axis of the distal humerus using a cadaver specimen
for in-vitro validation.
An approach for direct visualization of continuous three-dimensional elbow kinematics using reconstructed surfaces has
been developed. Simulation of valgus motion was achieved in five cadaveric specimens using an upper arm simulator.
Direct visualization of the motion of the ulna and humerus at the ulnohumeral joint was obtained using a contact based
registration technique. Employing fiducial markers, the rendered humerus and ulna were positioned according to the
simulated motion. The specific aim of this study was to investigate the effect of radial head arthroplasty on restoring
elbow joint stability after radial head excision. The position of the ulna and humerus was visualized for the intact elbow
and following radial head excision and replacement. Visualization of the registered humerus/ulna indicated an increase
in valgus angulation of the ulna with respect to the humerus after radial head excision. This increase in valgus angulation
was restored to that of an elbow with a native radial head following radial head arthroplasty. These findings were
consistent with previous studies investigating elbow joint stability following radial head excision and arthroplasty. The
current technique was able to visualize a change in ulnar position in a single DoF. Using this approach, the coupled
motion of ulna undergoing motion in all 6 degrees-of-freedom can also be visualized.
Incorrect selection of the native flexion-extension axis during implant alignment in elbow replacement surgery is likely a
significant contributor to failure of the prosthesis. Computer and image-assisted surgery is emerging as a useful surgical
tool in terms of improving the accuracy of orthopaedic procedures. This study evaluated the accuracy of implant
alignment using an image-based navigation technique compared against a conventional non-navigated approach.
Implant alignment error was 0.8 ± 0.3 mm in translation and 1.1 ± 0.4° in rotation for the navigated alignment, compared
with 3.1 ± 1.3 mm and 5.0 ± 3.8° for the non-navigated alignment. Five (5) of the 11 non-navigated alignments were
malaligned greater than 5° while none of the navigated alignments were placed with an error of greater than 2.0°. It is
likely that improved implant positioning will lead to reduced implant loading and wear, resulting in fewer implantrelated
complications and revision surgeries.
Commercially available orthopaedic implants used to replace a fractured or damaged radial head in the elbow are limited because the simplified axisymmetric design only approximates the normal bone anatomy. An implant that more closely approximates the normal anatomy of the radial head is likely to be superior to the ones of standard shapes and sizes. This paper provides a description of how reverse engineering technology is being used to replicate the geometry of the radial head from computer tomography imagery. Reverse engineering is the process of generating accurate 3D CAD models of free-form surfaces from measured coordinate data. In this application, shape information of the bone is extracted from CT images, translated into global coordinates, and transferred to a CAD software package in order to generate a solid model of the radial head region. The solid model is formed by creating contours from edge points, lofting these contours, and then joining the lofted contours. The tool-path for machining the implant device on a computer numerically controlled milling machine is generated from the solid model. The results of an experiment are presented in order to demonstrate the effectiveness of this approach to reverse engineering and manufacturing radial head replacements.
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