Magnetostriction-based force feedback for robot-assisted cardiovascular surgery using smart magnetorheological elastomers

A teleoperated robotic catheter operating system is a solution to avoid occupational hazards caused by repeated exposure radiation of the surgeon to X-ray during the endovascular procedures. However, inadequate force feedback and collision detection while teleoperating surgical tools elevate the risk of endovascular procedures. Moreover, surgeons cannot control the force of the catheter/guidewire within a proper range, and thus the risk of blood vessel damage will increase. In this paper, a magnetorheological fluid (MR)-based robot-assisted catheter/guidewire surgery system has been developed, which uses the surgeon’s natural manipulation skills acquired through experience and uses haptic cues to generate collision detection to ensure surgical safety. We present tests for the performance evaluation regarding the teleoperation, the force measurement, and the collision detection with haptic cues. Results show that the system can track the desired position of the surgical tool and detect the relevant force event at the catheter. In addition, this method can more readily enable surgeons to distinguish whether the proximal force exceeds or meets the safety threshold of blood vessels.

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Asymmetric force feedback control framework for teleoperated robot-assisted surgery

2013 IEEE International Conference on Robotics and Automation ◽

10.1109/icra.2013.6631411 ◽

2013 ◽

Cited By ~ 5

Author(s):

Omid Mohareri ◽

Septimiu E. Salcudean ◽

Christopher Nguan

Keyword(s):

Feedback Control ◽

Force Feedback ◽

Robot Assisted ◽

Control Framework ◽

Asymmetric Force ◽

Robot Assisted Surgery

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Real-Time 2D Surface Profile Mapping of Biological Tissue with Force Feedback in Robot-Assisted Minimally Invasive Surgery

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.798.319 ◽

2015 ◽

Vol 798 ◽

pp. 319-323

Author(s):

Ali Reza Hassan Beiglou ◽

Javad Dargahi

Keyword(s):

Minimally Invasive Surgery ◽

Minimally Invasive ◽

Real Time ◽

Invasive Surgery ◽

Strain Gauge ◽

Force Feedback ◽

Surface Profile ◽

Robot Assisted ◽

Contact Points ◽

Force Signal

It has been more than 20 years that robot-assisted minimally invasive surgery (RMIS) has brought remarkable accuracy and dexterity for surgeons along with the decreasing trauma for the patients. In this paper a novel method of the tissue’s surface profile mapping is proposed. The tissue surface profile plays an important role for material identification during RMIS. It is shown how by integrating the force feedback into robot controller the surface profile of the tissue can be obtained with force feedback scanning. The experiment setup includes a 5 degree of freedoms (DOFs) robot which is equipped with a strain-gauge ball caster as the force feedback. Robot joint encoders signals and the captured force signal of the strain-gauge are transferred to developed surface transformation algorithm (STA). The real-time geometrical transformation process is triggered with force signal to identify contact points between the ball caster and the artificial tissue. The 2D surface profile of tissue will be mapped based on these contact points. Real-time capability of the proposed system is evaluated experimentally for the artifical tissues in a designed test rig.

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A Vision-Based Approach for Estimating Contact Forces: Applications to Robot-Assisted Surgery

Applied Bionics and Biomechanics ◽

10.1155/2005/436897 ◽

2005 ◽

Vol 2 (1) ◽

pp. 53-60 ◽

Cited By ~ 2

Author(s):

C. W. Kennedy ◽

J. P. Desai

Keyword(s):

Finite Element ◽

Finite Element Model ◽

Real Time ◽

Force Feedback ◽

Element Model ◽

Robot Arm ◽

Robot Assisted ◽

Interaction Forces ◽

Fem Model ◽

Nodal Displacements

The primary goal of this paper is to provide force feedback to the user using vision-based techniques. The approach presented in this paper can be used to provide force feedback to the surgeon for robot-assisted procedures. As proof of concept, we have developed a linear elastic finite element model (FEM) of a rubber membrane whereby the nodal displacements of the membrane points are measured using vision. These nodal displacements are the input into our finite element model. In the first experiment, we track the deformation of the membrane in real-time through stereovision and compare it with the actual deformation computed through forward kinematics of the robot arm. On the basis of accurate deformation estimation through vision, we test the physical model of a membrane developed through finite element techniques. The FEM model accurately reflects the interaction forces on the user console when the interaction forces of the robot arm with the membrane are compared with those experienced by the surgeon on the console through the force feedback device. In the second experiment, the PHANToM haptic interface device is used to control the Mitsubishi PA-10 robot arm and interact with the membrane in real-time. Image data obtained through vision of the deformation of the membrane is used as the displacement input for the FEM model to compute the local interaction forces which are then displayed on the user console for providing force feedback and hence closing the loop.

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