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Finite Element Modeling of Electromagnetic-Coils Targeting System for Locating Distal Screw-Hole in Intramedullary Interlocking-Nail Surgery

[+] Author Affiliations
Ya-Wen Cheng, Po-Wen Chen, Chin-Chung Chen, Wensyang Hsu, Tien-Kan Chung

National Chiao Tung University, Hsinchu, Taiwan

Tze-Hong Wong

National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan

Paper No. ISPS-MIPE2018-8536, pp. V001T05A003; 3 pages
doi:10.1115/ISPS-MIPE2018-8536
From:
  • ASME-JSME 2018 Joint International Conference on Information Storage and Processing Systems and Micromechatronics for Information and Precision Equipment
  • ASME-JSME 2018 Joint International Conference on Information Storage and Processing Systems and Micromechatronics for Information and Precision Equipment
  • San Francisco, California, USA, August 29–30, 2018
  • Conference Sponsors: Information Storage and Processing Systems Division
  • ISBN: 978-0-7918-5193-7
  • Copyright © 2018 by ASME

abstract

In this paper, we report a finite element modeling of an electromagnetic-coils targeting system to locate a distal screw-hole in intramedullary interlocking-nail surgery. The system consists of an internal coil, external coil, and control/measurement electronics. The internal coil is embedded in a distal screw-hole of the nail inserted into the bone. A current is applied to the internal coil to produce a directional magnetic flux penetrating the nail/bone. Thus, the external coil scans different regions of the nail/bone will receive different amount of magnetic flux, and thereby produces different voltage outputs due to the electromagnetic induction. By analyzing the voltage outputs, the distal screw-hole is targeted. However, to precisely apply this system to many different nails for people in different regions, modification and optimization of the system are needed. For rapid modification and optimization, we implement finite element method to model the targeting system. Because the modeling results are qualitatively consistent to experimental results, the modeling is successfully validated to be able to qualitatively predict experimental trends and thereby can be used for rapid system modification and optimization.

Copyright © 2018 by ASME

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