Adaptive signal processing
On the Feasibility of a Moving Support for Surgery on the Beating Heart
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
A Novel Algorithm for Heart Motion Analysis Based on Geometric Constraints
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Cardiolock: an active cardiac stabilizer first in vivo experiments using a new robotized device
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Force tracking with feed-forward motion estimation for beating heart surgery
IEEE Transactions on Robotics
Soft-tissue motion tracking and structure estimation for robotic assisted MIS procedures
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Toward robotized beating heart TECABG: assessment of the heart dynamics using high-speed vision
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
International Journal of Computer Applications in Technology
Simultaneous stereoscope localization and soft-tissue mapping for minimal invasive surgery
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Integration of new features for telerobotic surgery into the MiroSurge system
Applied Bionics and Biomechanics - Surgical Robotics
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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.