Ultrasound-Guided Assistive Robots for Scoliosis Assessment With Optimization-Based Control and Variable Impedance

Anqing Duan, Maria Victorova, Jingyuan Zhao, Yuxiang Sun, Yongping Zheng, David Navarro-Alarcon

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Assistive robots for healthcare have witnessed a growing demand over the past decades. In this letter, we investigate the development of an optimization-based control framework with variable impedance for an assistive robot to perform ultrasound-guided scoliosis assessment. The conventional procedure for scoliosis assessment using ultrasound imaging typically requires a medical practitioner to slide an ultrasound probe along a patient's back while maintaining a certain magnitude of the contact force. To automate such a procedure, we need to consider multiple objectives, such as contact force, position, orientation, energy, posture, etc. To coordinate different objectives, we propose to formulate the control framework as a quadratic programming problem with each objective weighted by a tunable task priority, subject to a set of equality and inequality constraints. As the procedure requires the robot to establish a constant contact force with the patient during scanning, we incorporate variable impedance regulation of the end-effector to enhance safety and stability during the physical human-robot interaction; The variable impedance gains are then retrieved by learning from medical expert's demonstrations. The proposed methodology is evaluated with a robotic system performing autonomous scoliosis assessment with multiple human subjects involved. The effectiveness of our approach is verified by the coronal spinal images obtained with the robot.

Original languageEnglish
Pages (from-to)8106-8113
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume7
Issue number3
DOIs
Publication statusPublished - 1 Jul 2022

Keywords

  • learning from demonstration
  • Medical robots and systems
  • optimization and optimal control
  • physical human-robot interaction
  • task and motion planning

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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