3D Printing in Medicine (Jan 2018)
Feasibility study applying a parametric model as the design generator for 3D–printed orthosis for fracture immobilization
Abstract
Abstract Background Applying 3D printing technology for the fabrication of custom-made orthoses provides significant advantages, including increased ventilation and lighter weights. Currently, the design of such orthoses is most often performed in the CAD environment, but creating the orthosis model is a time-consuming process that requires significant CAD experience. This skill gap limits clinicians from applying this technology in fracture treatment. The purpose of this study is to develop a parametric model as the design generator for 3D–printed orthoses for an inexperienced CAD user and to evaluate its feasibility and ease of use via a training and design exercise. Results A set of automatic steps for orthosis modeling was developed as a parametric model using the Visual Programming Language in the CAD environment, and its interface and workflow were simplified to reduce the training period. A quick training program was formulated, and 5 participants from a nursing school completed the training within 15 mins. They verified its feasibility in an orthosis design exercise and designed 5 orthoses without assistance within 8 to 20 mins. The few faults and program errors that were observed in video analysis of the exercise showed improvable weaknesses caused by the scanning quality and modeling process. Conclusions Compared to manual modeling instruction, this study highlighted the feasibility of using a parametric model for the design of 3D–printed orthoses and its greater ease of use for medical personnel compared to the CAD technique. The parametric model reduced the complex process of orthosis design to a few minutes, and a customized interface and training program accelerated the learning period. The results from the design exercise accurately reflect real-world situations in which an inexperienced user utilizes a generator as well as demonstrate the utility of the parametric model approach and strategy for training and interfacing.
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