A Curved-Drilling Approach in Core Decompression of the Femoral Head Osteonecrosis Using a Continuum Manipulator

Farshid Alambeigi, Yu Wang, Shahriar Sefati, Cong Gao, Ryan J. Murphy, Iulian Iordachita, Russel H. Taylor, Harpal Khanuja, Mehran Armand

Research output: Contribution to journalArticle

Abstract

In conventional core decompression of osteonecrosis, surgeons cannot successfully reach the whole area of the femoral head due to rigidity of the instruments currently used. To address this issue, we present design and fabrication of a novel steerable drill using a continuum dexterous manipulator (CDM) and two different flexible cutting tools passing through the lumen of the CDM. A set of experiments investigated functionality and efficiency of the curved-drilling approach and the flexible tools on simulated cancellous bone. Geometry of the cutter head, rotational and feed velocity of the tool, and pulling tension of the CDM cables have been identified as the effective curved-drilling parameters. Considering these parameters, we investigated drilling trajectory, contact force, and mass removal for various combinations of feed-velocities (0.05, 0.10, and 0.15 mm/s) and cable tensions (6, 10, 15, and 25 N) with constant rotational speed of 2250 r/min. Results show that: first, pulling tension of the cable is the most dominant parameter affecting the curved-drilling trajectory; and second, the proposed steerable drill is able to achieve 40° bend without buckling. Based on these results we developed a method for planning drill trajectories and successfully verified abilities for S-shape and multiple-branch drilling. The verification experiments were performed on both simulated and human cadaveric bones.

Original languageEnglish (US)
Article number7855629
Pages (from-to)1480-1487
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume2
Issue number3
DOIs
StatePublished - Jul 2017

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Keywords

  • Continuum manipulator
  • core decompression
  • curved-drilling
  • medical robotics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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