Method of Forearm Muscles 3D Modeling Using Robotic Ultrasound Scanning.

Journal: Sensors (Basel, Switzerland)
PMID:

Abstract

The accurate assessment of muscle morphology and function is crucial for medical diagnostics, rehabilitation, and biomechanical research. This study presents a novel methodology for constructing volumetric models of forearm muscles based on three-dimensional ultrasound imaging integrated with a robotic system to ensure precise probe positioning and controlled pressure application. The proposed ultrasound scanning approach combined with a collaborative six-degrees-of-freedom robotic manipulator enabled reproducible and high-resolution imaging of muscle structures in both relaxed and contracted states. A custom-built phantom, acoustically similar to biological tissues, was developed to validate the method. The cross-sectional area of the muscles and the coordinates of the center of mass of the sections, as well as the volume and center of gravity of each muscle, were calculated for each cross-section of the reconstructed forearm muscle models at contraction. The method's feasibility was confirmed by comparing the reconstructed volumes with anatomical data and phantom measurements. This study highlights the advantages of robotic-assisted ultrasound imaging for non-invasive muscle assessment and suggests its potential applications in neuromuscular diagnostics, prosthetics design, and rehabilitation monitoring.

Authors

  • Vladislava Kapravchuk
    Department of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
  • Albert Ishkildin
    Department of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
  • Andrey Briko
    Department of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
  • Anna Borde
    Department of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
  • Maria Kodenko
    Department of Biomedical Technologies, Bauman Moscow State Technical University, 105005 Moscow, Russia.
  • Anastasia Nasibullina
    Moscow Center for Diagnostics and Telemedicine, 101990 Moscow, Russia.
  • Sergey Shchukin
    Department of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.