Force-assisted ultrasound imaging system through dual force sensing and admittance robot control

Ting Yun Fang, Haichong K. Zhang, Rodolfo Finocchi, Russell H. Taylor, Emad Boctor

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Purpose: Ultrasound imaging has been a gold standard for clinical diagnoses due to its unique advantages compared to other imaging modalities including: low cost, noninvasiveness, and safeness to the human body. However, the ultrasound scanning process requires applying a large force over extended periods of time, often in uncomfortable postures in order to maintain the desired orientation. This physical requirement over sonographers’ careers often leads to musculoskeletal pain and strain injuries. Methods: To address this problem, we propose a cooperatively controlled robotic ultrasound system to reduce the force sonographers apply. The proposed system consists of two key components: a six-axis robotic arm that holds and actuates the ultrasound probe, and a dual force sensor setup that enables cooperative control and adaptive force assistance. With the admittance force control, the robotic arm complies with the motion of the operator, while assisting with force during the scanning. Results: We validated the system through a user study involving expert sonographers and lay people and demonstrated 32–73% reduction in human applied force and 8– 18% improvement in image stability. Conclusion: These results indicate that the system has the potential to not only reduce the burden on the sonographer, but also provide more stable ultrasound scanning.

Original languageEnglish (US)
Pages (from-to)983-991
Number of pages9
JournalInternational Journal of Computer Assisted Radiology and Surgery
Issue number6
StatePublished - Jun 1 2017


  • Admittance control
  • Co-robotic ultrasound
  • Cooperative robot control
  • Dual force sensing
  • Force-assisted

ASJC Scopus subject areas

  • Surgery
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design


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