Multi-Magnet Tracking Method using Extended Kalman Filter*

Abstract

Permanent magnet-based localization can provide a wireless and low-cost solution for tracking surgical instruments in Minimally Invasive Surgery (MIS). To meet the requirement of simultaneously tracking of multiple surgical instruments in clinical application scenarios, we propose a probabilistic filtering approach to realize multi-magnet positioning. The tracking system includes a magnetic sensor array and magnetic targets. Random walk model has been used to formulate the system equation, and the measurement equation is established with the magnetic dipole model. Based on the Extended Kalman Filter (EKF) algorithm, the nonlinear problem can be solved by estimating the positions and orientations of multiple magnets. The feasibility of the proposed method is verified by both static and dynamic experiments. The results show that the filtering-based multi-target magnetic tracking algorithm enables low-latency tracking with reasonable accuracy.