• DocumentCode
    2392520
  • Title

    Hybrid attitude estimation for laparoscopic surgical tools: A preliminary study

  • Author

    Ren, Hongliang ; Kazanzides, Peter

  • Author_Institution
    Dept. of Biomed. Eng., Johns Hopkins Univ., Baltimore, MD, USA
  • fYear
    2009
  • fDate
    3-6 Sept. 2009
  • Firstpage
    5583
  • Lastpage
    5586
  • Abstract
    Laparoscopic surgery poses a challenging problem for a real-time navigation system: how to keep tracking the surgical tools inside the human body intraoperatively. This paper proposes a sensor fusion method for a hybrid tracking system that incorporates a miniature inertial measurement unit and an electromagnetic navigation system, in order to obtain continuous orientation information, even in the presence of metal objects. The sensor fusion algorithm employs an extended Kalman filter to integrate the data from the two sensor streams, based on a quaternion formulation of the system dynamics. The preliminary experimental results show that the integration of low-cost inertial measurement is able to compensate the distortion of EM tracking.
  • Keywords
    Kalman filters; inertial navigation; medical robotics; medical signal processing; optical tracking; sensor fusion; surgery; EM tracking; continuous orientation information; electromagnetic navigation system; extended Kalman filter; hybrid attitude estimation; laparoscopic surgical tools; metal objects; miniature inertial measurement; quaternion formulation; sensor fusion; system dynamics; Extended Kalman Filter; Laparoscopic surgery; Sensor fusion; surgical navigation; Acceleration; Algorithms; Equipment Design; Equipment Failure Analysis; Humans; Laparoscopes; Magnetics; Pilot Projects; Reproducibility of Results; Sensitivity and Specificity; Surgery, Computer-Assisted; Systems Integration; Transducers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-3296-7
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2009.5333487
  • Filename
    5333487