Surgical motion adaptive robotic technology (S.M.A.R.T): Taking the motion out of physiological motion

Abstract

In precision computer and robotic assisted minimally invasive surgical procedures, such as retinal microsurgery or cardiac bypass surgery, physiological motion can hamper the surgeon’s ability to effectively visualize and approach the target site. Current day stabilizers used for minimally invasive cardiac surgery often stretch or pull at the tissue, causing subsequent tissue damage. In this study, we investigated novel means of modeling Z-axis physiological motion and demonstrate how these models could be used to compensate for this motion in order to provide a more stable surgical field. The Z-axis motion compensation is achieved by using a fiber-optic laser sensor to obtain precise displacement measurements. Using a weighted time series modeling technique, modeling of rodent chest wall motion and heart wall motion was accomplished. Our computational methods for modeling physiological motion open the door for applications using high speed, high precision actuators to filter motion out and provide for a stable surgical field.