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Development of a control algorithm for the ultrasound scanning robot (NCCUSR) using ultrasound image and force feedback
Author(s) -
Kim Yeoun Jae,
Seo Jong Hyun,
Kim Hong Rae,
Kim Kwang Gi
Publication year - 2017
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1756
Subject(s) - robot , computer science , ultrasound , artificial intelligence , imaging phantom , 3d ultrasound , computer vision , simulation , medicine , radiology
Abstract Background Clinicians who frequently perform ultrasound scanning procedures often suffer from musculoskeletal disorders, arthritis, and myalgias. To minimize their occurrence and to assist clinicians, ultrasound scanning robots have been developed worldwide. Although, to date, there is still no commercially available ultrasound scanning robot, many control methods have been suggested and researched. These control algorithms are either image based or force based. If the ultrasound scanning robot control algorithm was a combination of the two algorithms, it could benefit from the advantage of each one. However, there are no existing control methods for ultrasound scanning robots that combine force control and image analysis. Therefore, in this work, a control algorithm is developed for an ultrasound scanning robot using force feedback and ultrasound image analysis. Methods A manipulator‐type ultrasound scanning robot named ‘NCCUSR’ is developed and a control algorithm for this robot is suggested and verified. First, conventional hybrid position–force control is implemented for the robot and the hybrid position–force control algorithm is combined with ultrasound image analysis to fully control the robot. The control method is verified using a thyroid phantom. Results It was found that the proposed algorithm can be applied to control the ultrasound scanning robot and experimental outcomes suggest that the images acquired using the proposed control method can yield a rating score that is equivalent to images acquired directly by the clinicians. Conclusions The proposed control method can be applied to control the ultrasound scanning robot. However, more work must be completed to verify the proposed control method in order to become clinically feasible. Copyright © 2016 John Wiley & Sons, Ltd.