Heart phase estimation using directional statistics for robotic beating heart surgery

Robotic beating heart surgery requires accurate information about the current state of the heart. For this purpose, it is of great importance to have a good estimate of the heart's current phase, which in essence corresponds to the percentage of the current heart cycle that has already passed. Estimation of the heart phase is a highly nontrivial problem as the heart motion is not exactly periodic. On the contrary, it varies slightly from beat to beat and changes in frequency over time. In order to derive a robust phase estimation algorithm, we rely on directional statistics, a subfield of statistics that deals with quantities that are inherently periodic, such as the phase of the beating heart. The proposed methods are evaluated on a real data set and shown to be superior to the state of the art.