Multisensor Data Fusion in an Integrated Tracking System for Endoscopic Surgery

Abstract

Surgical planning and navigation systems are vital for minimally invasive endoscopic surgeries but it is challenging to track the position and orientation of intrabody surgical instruments in these procedures. In order to address this problem, we propose a tracking system including multiple-sensor integration and data fusion. The proposed tracking approach is free of the constraints of line-of-sight, less subject to environmental distortion, and with higher update rate. By incorporating electromagnetic and inertial sensors, the system yields continuous 6-DOF information. Based on a system dynamic model and estimation theories, a new multisensor fusion algorithm, cascade orientation and position-estimation algorithm, is proposed for the integrated tracking device. The experimental results show that the proposed algorithms achieve accurate orientation and position tracking with robustness.