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Design and construction of a wireless robot that simulates head movements in cone beam computed tomography imaging

Published online by Cambridge University Press:  01 August 2022

R. Baghbani*
Affiliation:
Department of Biomedical Engineering, Hamedan University of Technology, Hamedan, Iran
M. Ashoorirad
Affiliation:
Department of Biomedical Engineering, Hamedan University of Technology, Hamedan, Iran
F. Salemi
Affiliation:
Department of Oral and Maxillofacial Radiology, Dental School, Hamadan University of Medical Sciences, Hamadan, Iran
Med Amine Laribi
Affiliation:
Department of GMSC, Pprime Institute CNRS, ENSMA, UPR 3346, University of Poitiers, Poitiers, France
M. Mostafapoor
Affiliation:
Department of Oral and Maxillofacial Radiology, Dental School, Hamadan University of Medical Sciences, Hamadan, Iran
*
*Corresponding author. E-mail: baghbani@hut.ac.ir

Abstract

One of the major challenges in the science of maxillofacial radiology imaging is the various artifacts created in images taken by cone beam computed tomography (CBCT) imaging systems. Among these artifacts, motion artifact, which is created by the patient, has adverse effects on image quality. In this paper, according to the conditions and limitations of the CBCT imaging room, the goal is the design and development of a cable-driven parallel robot to create repeatable movements of a dry skull inside a CBCT scanner for studying motion artifacts and building up reference datasets with motion artifacts. The proposed robot allows a dry skull to execute motions, which were selected on the basis of clinical evidence, with 3-degrees of freedom during imaging in synchronous manner with the radiation beam. The kinematic model of the robot is presented to investigate and describe the correlation between the amount of motion and the pulse width applied to DC motors. This robot can be controlled by the user through a smartphone or laptop wirelessly via a Wi-Fi connection. Using wireless communication protects the user from harmful radiation during robot driving and functioning. The results show that the designed robot has a reproducibility above 95% in performing various movements.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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