Physiological motion modeling for organ-mounted robots
Abstract
Background: Organ-mounted robots passively compensate heartbeat and respiratory motion. In model-guided procedures, this motion can be a significant source of information that can be used to aid in localization or to add dynamic information to static preoperative maps.
Methods: Models for estimating periodic motion are proposed for both position and orientation. These models are then tested on animal data and optimal orders are identified. Finally, methods for online identification are demonstrated.
Results: Models using exponential coordinates and Euler-angle parameterizations are as accurate as models using quaternion representations, yet require a quarter fewer parameters. Models which incorporate more than 4 cardiac or 3 respiration harmonics are no more accurate. Finally, online methods estimate model parameters as accurately as offline methods within 3 respiration cycles.
Conclusions: These methods provide a complete framework for accurately modelling the periodic deformation of points anywhere on the surface of the heart in a closed chest.
BibTeX
@article{Wood-2017-110282,author = {Nathan A. Wood and David Schwartzman and Marco A. Zenati and Cameron N. Riviere},
title = {Physiological motion modeling for organ-mounted robots},
journal = {International Journal of Medical Robotics and Computer Assisted Surgery},
year = {2017},
month = {December},
volume = {13},
number = {4},
pages = {e1805},
keywords = {medical robotics, cardiac surgery, physiological motion compensation},
}