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Augmented Reality Based Navigation for Computer Assisted Hip Resurfacing: A Proof of Concept Study

Overview of attention for article published in Annals of Biomedical Engineering, May 2018
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Title
Augmented Reality Based Navigation for Computer Assisted Hip Resurfacing: A Proof of Concept Study
Published in
Annals of Biomedical Engineering, May 2018
DOI 10.1007/s10439-018-2055-1
Pubmed ID
Authors

He Liu, Edouard Auvinet, Joshua Giles, Ferdinando Rodriguez y Baena

Abstract

Implantation accuracy has a great impact on the outcomes of hip resurfacing such as recovery of hip function. Computer assisted orthopedic surgery has demonstrated clear advantages for the patients, with improved placement accuracy and fewer outliers, but the intrusiveness, cost, and added complexity have limited its widespread adoption. To provide seamless computer assistance with improved immersion and a more natural surgical workflow, we propose an augmented-reality (AR) based navigation system for hip resurfacing. The operative femur is registered by processing depth information from the surgical site with a commercial depth camera. By coupling depth data with robotic assistance, obstacles that may obstruct the femur can be tracked and avoided automatically to reduce the chance of disruption to the surgical workflow. Using the registration result and the pre-operative plan, intra-operative surgical guidance is provided through a commercial AR headset so that the user can perform the operation without additional physical guides. To assess the accuracy of the navigation system, experiments of guide hole drilling were performed on femur phantoms. The position and orientation of the drilled holes were compared with the pre-operative plan, and the mean errors were found to be approximately 2 mm and 2°, results which are in line with commercial computer assisted orthopedic systems today.

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The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 17%
Student > Master 12 13%
Researcher 6 7%
Student > Doctoral Student 6 7%
Student > Bachelor 6 7%
Other 17 19%
Unknown 27 30%
Readers by discipline Count As %
Medicine and Dentistry 21 24%
Engineering 15 17%
Computer Science 10 11%
Neuroscience 3 3%
Nursing and Health Professions 1 1%
Other 4 4%
Unknown 35 39%