Prediction of heartbeat motion with a generalized adaptive filter

In order to perform coronary artery bypass graft surgery, a stationary heart is necessary. A human cannot achieve manual tracking of the complex heartbeat motion. Robotics technology can overcome such limitations. In the robotic-assisted beating heart surgery, the robot actively cancels heart motion by closely following a point of interest on the heart surface-a process called Active Relative Motion Canceling. As a result, surgeon can operate on the beating heart as if it is stationary. In this paper, a generalized estimation algorithm, that uses an adaptive filter to generate future position estimates is studied. The predictor is parameterized on-line and adaptively to minimize the prediction error in the mean-square sense. The predictor is evaluated using a 3-degree-of-freedom test-bed system and prerecorded heart motion data.