scholarly journals Estimating Tool–Tissue Forces Using a 3-Degree-of-Freedom Robotic Surgical Tool

2016 ◽  
Vol 8 (5) ◽  
Author(s):  
Baoliang Zhao ◽  
Carl A. Nelson
Keyword(s):  
Force Feedback ◽  
Estimation Method ◽  
Interaction Force ◽  
Normal Function ◽  
Degree Of Freedom ◽  
Force Estimation ◽  
Robot Assisted ◽  
Interaction Forces ◽  
Tissue Interaction ◽  
Surgical Tool

Robot-assisted minimally invasive surgery (MIS) has gained popularity due to its high dexterity and reduced invasiveness to the patient; however, due to the loss of direct touch of the surgical site, surgeons may be prone to exert larger forces and cause tissue damage. To quantify tool–tissue interaction forces, researchers have tried to attach different kinds of sensors on the surgical tools. This sensor attachment generally makes the tools bulky and/or unduly expensive and may hinder the normal function of the tools; it is also unlikely that these sensors can survive harsh sterilization processes. This paper investigates an alternative method by estimating tool–tissue interaction forces using driving motors' current, and validates this sensorless force estimation method on a 3-degree-of-freedom (DOF) robotic surgical grasper prototype. The results show that the performance of this method is acceptable with regard to latency and accuracy. With this tool–tissue interaction force estimation method, it is possible to implement force feedback on existing robotic surgical systems without any sensors. This may allow a haptic surgical robot which is compatible with existing sterilization methods and surgical procedures, so that the surgeon can obtain tool–tissue interaction forces in real time, thereby increasing surgical efficiency and safety.

scholarly journals A Magnetorheological Fluids-Based Robot-Assisted Catheter/Guidewire Surgery System for Endovascular Catheterization

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 640
Author(s):  
Linshuai Zhang ◽  
Shuoxin Gu ◽  
Shuxiang Guo ◽  
Takashi Tamiya
Keyword(s):  
Collision Detection ◽  
Endovascular Procedures ◽  
Force Feedback ◽  
Force Measurement ◽  
Occupational Hazards ◽  
Robot Assisted ◽  
X Ray ◽  
Surgical Safety ◽  
Surgical Tool ◽  
Haptic Cues

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.

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

2005 ◽  
Vol 2 (1) ◽  
pp. 53-60 ◽  
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.

Tool-Tissue Force Estimation for a 3-DOF Robotic Surgical Tool

2015 ◽  
Author(s):  
Baoliang Zhao ◽  
Carl A. Nelson
Keyword(s):  
Haptic Feedback ◽  
Estimation Method ◽  
Tissue Reaction ◽  
Limiting Factor ◽  
Haptic Interfaces ◽  
Force Estimation ◽  
Surgical Tools ◽  
Motor Current ◽  
Surgical Tool ◽  
Reaction Forces

Robotic minimally invasive surgery has achieved success in various procedures; however, the lack of haptic feedback is considered by some to be a limiting factor. The typical method to acquire tool-tissue reaction forces is attaching force sensors on surgical tools, but this complicates sterilization and makes the tool bulky. This paper explores the feasibility of using motor current to estimate tool-tissue forces, and demonstrates acceptable results in terms of time delay and accuracy. This sensorless force estimation method sheds new light on the possibility of equipping existing robotic surgical systems with haptic interfaces that require no sensors and are compatible with existing sterilization methods.

Master-slave control and evaluation of force sensing for robot-assisted minimally invasive surgery

2020 ◽  
Vol 47 (6) ◽  
pp. 903-914
Author(s):  
Kun Li ◽  
Shuai Ji ◽  
Guojun Niu ◽  
Yue Ai ◽  
Bo Pan ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Control Strategy ◽  
Force Feedback ◽  
Ex Vivo ◽  
Force Sensing ◽  
Surgical Instrument ◽  
Blunt Dissection ◽  
Robot Assisted ◽  
Interaction Forces ◽  
Content Type

Purpose Existing robot-assisted minimally invasive surgery (RMIS) system lacks of force feedback, and it cannot provide the surgeon with interaction forces between the surgical instruments and patient’s tissues. This paper aims to restore force sensation for the RMIS system and evaluate effect of force sensing in a master-slave manner. Design/methodology/approach This paper presents a four-DOF surgical instrument with modular joints and six-axis force sensing capability and proposes an incremental position mode master–slave control strategy based on separated position and orientation to reflect motion of the end of master manipulator to the end of surgical instrument. Ex-vivo experiments including tissue palpation and blunt dissection are conducted to verify the effect of force sensing for the surgical instrument. An experiment of trajectory tracking is carried out to test precision of the control strategy. Findings Results of trajectory tracking experiment show that this control strategy can precisely reflect the hand motion of the operator, and the results of the ex-vivo experiments including tissue palpation and blunt dissection illustrate that this surgical instrument can measure the six-axis interaction forces successfully for the RMIS. Originality/value This paper addresses the important role of force sensing and force feedback in RMIS, clarifies the feasibility to apply this instrument prototype in RMIS for force sensing and provides technical support of force feedback for further clinical application.

Development of an Instrumented Surgical Setup for Quantifying Displacement and Force in Surgical Dissection

2015 ◽  
Author(s):  
K. C. Wang ◽  
K. Grant ◽  
Q. Sun ◽  
L. S. Gan ◽  
K. Zareinia ◽  
...  
Keyword(s):  
Brain Structures ◽  
Interaction Force ◽  
Computational Techniques ◽  
Interaction Forces ◽  
Mean Values ◽  
Surgical Simulators ◽  
Tissue Interaction ◽  
Force Components ◽  
Sylvian Cistern ◽  
Force Data

Knowledge of positional and force properties of surgical dissection in neurosurgery is essential in developing simulation platforms for neurosurgical training such that realistic motion and perception can be conveyed to the trainee during practice. Most proposed models in literature utilize computational techniques to formulate required parameters. However, these models are not realistic enough compared to data obtained from experiments on real brain. Therefore, developing a setup to measure the position, orientation, and interaction forces will help researchers formulate realistic parameters. This paper presents the development of such a setup for quantification of displacements and tool-tissue interaction forces during performance of microsurgical tasks. A bipolar forceps is equipped with a set of force sensing elements to measure the tool-tissue interaction force components. The position and orientation of the forceps tips are measured by attaching a tracker to the bipolar forceps. To show proof-of-concept, an experienced surgeon and one assistant surgeon performed 35 neurosurgical tasks (320 trials) on a cadaver brain (previously-frozen) using the instrumented setup. Positional and force data of the bipolar forceps were recorded during surgical dissection of different brain structures. This paper reports results collected from two microsurgical tasks over 40 trials: dissection of sylvian cistern arachnoid (SCA) and dissection of middle cerebral artery (MCA). Results showed that the mean values of interaction forces during dissection of MCA were smaller than dissecting SCA. The maximum forces observed were 1.94 N and 1.75 N for SCA and MCA, respectively. The application of quantifying such parameters using the developed setup will be in training neurosurgery residents using surgical simulators in which the knowledge of brain tissue parameters is required to formulate the tissue model.

scholarly journals Vision-Based Suture Tensile Force Estimation in Robotic Surgery

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 110
Author(s):  
Won-Jo Jung ◽  
Kyung-Soo Kwak ◽  
Soo-Chul Lim
Keyword(s):  
Force Feedback ◽  
Short Term Memory ◽  
Tensile Force ◽  
Force Sensor ◽  
Interaction Force ◽  
Force Estimation ◽  
Training Experience ◽  
Pulling Force

Compared to laparoscopy, robotics-assisted minimally invasive surgery has the problem of an absence of force feedback, which is important to prevent a breakage of the suture. To overcome this problem, surgeons infer the suture force from their proprioception and 2D image by comparing them to the training experience. Based on this idea, a deep-learning-based method using a single image and robot position to estimate the tensile force of the sutures without a force sensor is proposed. A neural network structure with a modified Inception Resnet-V2 and Long Short Term Memory (LSTM) networks is used to estimate the suture pulling force. The feasibility of proposed network is verified using the generated DB, recording the interaction under the condition of two different artificial skins and two different situations (in vivo and in vitro) at 13 viewing angles of the images by changing the tool positions collected from the master-slave robotic system. From the evaluation conducted to show the feasibility of the interaction force estimation, the proposed learning models successfully estimated the tensile force at 10 unseen viewing angles during training.

A Class of 2-Degree-of-Freedom Planar Remote Center-of-Motion Mechanisms Based on Virtual Parallelograms

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Jianmin Li ◽  
Guokai Zhang ◽  
Yuan Xing ◽  
Hongbin Liu ◽  
Shuxin Wang
Keyword(s):  
Synthesis Method ◽  
Body Cavity ◽  
Degree Of Freedom ◽  
Three Dimension ◽  
Robot Assisted ◽  
Revolute Joints ◽  
3D Space ◽  
Surgical Tool ◽  
Main Components ◽  
Actuated Joints

Robot-assisted minimally invasive surgery (MIS) has shown tremendous advances over the traditional technique. The remote center-of-motion (RCM) mechanism is one of the main components of a MIS robot. However, the widely used planar RCM mechanism, with double parallelogram structure, requires an active prismatic joint to drive the surgical tool move in–out of the patient’s body cavity, which restricts the dexterity and the back-drivability of the robot to some extent. To solve this problem, a two degree-of-freedom (DOF) planar RCM mechanism type synthesis method is proposed. The basic principle is to construct virtual double parallelogram structure at any instant during the mechanism movements. Different with the existing ones, both of the actuated joints of the obtained RCM mechanism are revolute joints. Combining the proposed mechanism with a revolute joint whose axis passes through the RCM point to drive the whole mechanism out of the plane, the spatial RCM mechanisms to manipulate surgical tool in three-dimension (3D) space can be obtained; and the 3D RCM mechanism can be used for manipulating multi-DOF instruments in a robot-assisted MIS or can be used as an external positioner in robotic single-port surgeries.

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