An Application of Extended Kalman Filter for the Pressure Estimation in Minimally Invasive Surgery

Abstract

The paper presents an application of the Extended Kalman Filter (EKF) as an observer method to estimate the pressure in the operation area for the controlled process of minimally invasive surgery (MIS). Via trocars and pipes, the inflow and outflow of the rinsing fluid at the operation area are controlled by a double roller pump (DRP). Additionally, those flows are affected by the inside pressure of the pipes. The pressure sensor in the operation area is not allowed to utilize for surgery on the real patients at the current stage. Therefore, it is necessary to reconstruct the state of pressure in the operation area of MIS. The estimated pressure from the EKF estimator is used to replace the measured feedback signal to control the pump. The EKF worked based on the input signals of the rinsing fluid flows and the observable signal from available pressure sensors at the double roller pump. The proposed method was successfully implemented on MATLAB Simulink. For the further verification, it was also applied on the real device simulator environment. The results from the research show that the estimated pressure gives a high precision. In addition, the noises from the measured states are effectively eliminated.

Van-Muot Nguyen is currently a Ph.D. Candidate at the University of Rostock, Germany. He has worked at Can Tho University, Can Tho city, Vietnam (corresponding author’s phone number: +49-152-172-00738; fax: +49-381-498-7702).