Magnetic foreign body location based on least squares and extended Kalman filter

Abstract

The accurate and noninvasive localization of ferromagnetic objects in the human body for surgical removal is a healthcare demand. There are studies focused on enhancing the method and low-cost magnetometers’ sensitivity. This work focuses on improving the inverse problem algorithm for locating the ferromagnetic object in humans, using two models: least-squares and extended Kalman filter. Tests simulating sensor scans were performed using Matlab to check their performance and see which is the most robust. The least-squares method proved to be the most satisfactory method for the problem.

Keywords

• Magnetic foreign bodies
• Extended Kalman filter
• Least squares method