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腹腔镜手术工具的混合姿态估计:一项初步研究。

Hybrid attitude estimation for laparoscopic surgical tools: a preliminary study.

作者信息

Ren Hongliang, Kazanzides Peter

机构信息

The Laboratory for Computational Sensing and Robotics, Department of Biomedical Engineering, The Johns Hopkins University.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:5583-6. doi: 10.1109/IEMBS.2009.5333487.

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.

摘要

腹腔镜手术对实时导航系统提出了一个具有挑战性的问题

如何在手术过程中持续跟踪人体内的手术工具。本文提出了一种用于混合跟踪系统的传感器融合方法,该系统结合了微型惯性测量单元和电磁导航系统,以便即使在存在金属物体的情况下也能获得连续的方向信息。传感器融合算法采用扩展卡尔曼滤波器,基于系统动力学的四元数公式来整合来自两个传感器数据流的数据。初步实验结果表明,低成本惯性测量的融合能够补偿电磁跟踪的失真。

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