Daniel Glozman1, Moshe Shoham. 1. Mechanical Engineering Department, Technion - Israel Institute of Technology, Haifa, Israel. glozmand@technion.ac.il
Abstract
OBJECTIVE: A robotic system is presented for flexible needle steering and control in soft tissue. MATERIALS AND METHODS: Flexible needle insertion into a deformable tissue is modeled as a linear beam supported by virtual springs, where the stiffness coefficients of the springs can vary along the needle. Using this simplified model, the forward and inverse kinematics of the needle are solved analytically, thus enabling both path planning and path correction in real time. Given target and obstacle locations, the computer calculates the needle tip trajectory that will avoid the obstacle and hit the target. Using the inverse kinematics algorithm, the corresponding needle base maneuver needed to follow this trajectory is calculated. RESULTS: It is demonstrated that the needle tip path is not unique and can be optimized to minimize lateral pressure of the needle body on the tissue. Needle steering, i.e., the needle base movements that steer the needle tip, is not intuitive. Therefore, the needle insertion procedure is best performed by a robot. The model was verified experimentally on muscle and liver tissues by robotically assisted insertion of a flexible spinal needle. During insertion, the position and shape of the needle were recorded by X-ray. CONCLUSIONS: This study demonstrates the ability to curve a flexible needle by its base motion in order to achieve a planned tip trajectory.
OBJECTIVE: A robotic system is presented for flexible needle steering and control in soft tissue. MATERIALS AND METHODS: Flexible needle insertion into a deformable tissue is modeled as a linear beam supported by virtual springs, where the stiffness coefficients of the springs can vary along the needle. Using this simplified model, the forward and inverse kinematics of the needle are solved analytically, thus enabling both path planning and path correction in real time. Given target and obstacle locations, the computer calculates the needle tip trajectory that will avoid the obstacle and hit the target. Using the inverse kinematics algorithm, the corresponding needle base maneuver needed to follow this trajectory is calculated. RESULTS: It is demonstrated that the needle tip path is not unique and can be optimized to minimize lateral pressure of the needle body on the tissue. Needle steering, i.e., the needle base movements that steer the needle tip, is not intuitive. Therefore, the needle insertion procedure is best performed by a robot. The model was verified experimentally on muscle and liver tissues by robotically assisted insertion of a flexible spinal needle. During insertion, the position and shape of the needle were recorded by X-ray. CONCLUSIONS: This study demonstrates the ability to curve a flexible needle by its base motion in order to achieve a planned tip trajectory.
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