title: Hybrid attitude estimation for laparoscopic surgical tools: a preliminary study.
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.
authors: The Laboratory for Computational Sensing and Robotics, Department of Biomedical Engineering, The Johns Hopkins University. hlren@jhu.edu
authors: Hongliang
authors: H
authors: Ren
authors: Peter
authors: P
authors: Kazanzides
mesh_terms: D000054:Acceleration; D000465:Algorithms; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D020706:Laparoscopes; D008280:Magnetics / Q000295:instrumentation*; D010865:Pilot Projects; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D018511:Systems Integration; D014159:Transducers