Interventional Surgery Robot Research Articles

Design and Performance Evaluation of a Novel Vascular Interventional Surgery Robot

Introduction: Minimally invasive interventional surgical robots are used as delivery tools to assist healthcare professionals with medical devices such as micro guidewires and microcatheters during surgical treatment of cardiovascular and cerebrovascular obstruction, thus reducing surgical fatigue and radiation for healthcare professionals. Method: In this paper, a new vascular interventional surgical robot with multiple degrees of freedom is designed, its mechanism principle and movement mode is discussed in detail, and a prototype prototype is fabricated to make it simulate and reproduce the doctor's hand movements. Results: Through Abaqus simulation and platform experiments, the performance of the surgical robot is evaluated and analyzed from the perspectives of micro guidewire delivery displacement accuracy and radial clamping force for its high accuracy, high reliability, and safety. Conclusion: The results demonstrate that its surgical robot meets the requirements of providing vessel wall overload protection while the microcatheter delivery positioning accuracy error is less than 1 mm.

An unsupervised learning-based guidewire shape registration for vascular intervention surgery robot

In a vascular interventional surgery robot(VISR), a high transparency master-slave system can aid physicians in the more precise manipulation of guidewires for navigation and operation within blood vessels. However, deformations arising from the movement of the guidewire can affect the accuracy of the registration, thus reducing the transparency of the master-slave system. In this study, the degree of the guidewire’s deformation is analyzed based on the Kirchhoff model. An unsupervised learning-based guidewire shape registration method(UL-GSR) is proposed to estimate geometric transformations by learning displacement field functions. It can effectively achieve precise registration of flexible bodies. This method not only demonstrates high registration accuracy but also performs robustly under different complexity degrees of guidewire shapes. The experiments have demonstrated that the UL-GSR method significantly improves the accuracy of shape point set registration between the master and slave sides, thus enhancing the transparency and operational reliability of the VISR system.

TCN-Based Distal Force Feedback Strategy of a Vascular Interventional Surgery Robot

TCN-Based Distal Force Feedback Strategy of a Vascular Interventional Surgery Robot

Improved precise guidewire delivery of a cardiovascular interventional surgery robot based on admittance control.

The development of cardiovascular interventional surgery robots can realize master-slave interventional operations, which will effectively solve the problem of surgeons being injured by X-ray radiation. The delivery accuracy and safety of interventional instruments such as guidewire are the most important issues in the development of robotic systems. Most of the current control methods are position control or force feedback control, which cannot take into account delivery accuracy and safety. A cardiovascular interventional surgery robotic system integrated force sensors is developed. A novel force/position controller, which includes a radial basis function neural networks-based inner loop position controller and a force-based admittance outer loop controller, is proposed. Furthermore, a series of simulations and vascular model experiments are carried out to demonstrate the feasibility and accuracy of the proposed controller. The designed cardiovascular interventional robot is flexible to enter the target vessel branch. Experimental results indicate that the proposed controller can effectively improve the delivery accuracy of the guidewire and reduce the contact force with the vessel wall. The proposed controller based on radial basis function neural network and admittance control is effective in improving delivery accuracy and reducing contact force. The algorithm needs to be further validated in vivo experiments.

A Novel Master-Slave Interventional Surgery Robot with Force Feedback and Collaborative Operation.

In recent years, master-slave vascular robots have been developed to address the problem of radiation exposure during vascular interventions for surgeons. However, the single visual feedback reduces surgeon immersion and transparency of the system. In this work, we have developed a haptic interface based on the magnetorheological fluid (MRF) on the master side. The haptic interface can provide passive feedback force with high force fidelity and low inertia. Additionally, the manipulation of the master device does not change the operating posture of traditional surgery, which allows the surgeon to better adapt to the robotic system. For the slave robot, the catheter and guidewire can be navigated simultaneously which allows the two degrees of action on the catheter and axial action of a guidewire. The resistance force of the catheter navigation is measured and reflected to the user through the master haptic interface. To verify the proposed master-slave robotic system, the evaluation experiments are carried out in vitro, and the effectiveness of the system was demonstrated experimentally.

Grasping-Force-Based Passive Safety Method for a Vascular Interventional Surgery Robot System

Grasping-Force-Based Passive Safety Method for a Vascular Interventional Surgery Robot System

Design and Evaluation of a Learning-Based Vascular Interventional Surgery Robot

Interventional therapy is one of the most effective methods for diagnosing and treating vascular-related diseases at present. It relies on achieving precise and safe navigation of intravascular tools within a patient’s vasculature. Vascular Interventional Surgical Robots (VISR) can reduce surgeons’ exposure to operational hazards including radiation. However, the absence of apt position control and force feedback remains a challenge. This study presents an isomorphic master–slave VISR for precise navigation of endovascular tools viz. catheters and guidewires. The master console aids operators in issuing manipulation commands and logs feedback from the force, rotation, and translation data. The slave manipulator uses the commands received from the master platform for actual tool navigation. However, precise master–slave position control and force feedback are precursors for optimal patient outcomes. This study utilized a fuzzy-PID controller for precise tool navigation and a neural network model for resistance force modulation with 50 mN precision. Furthermore, we evaluated the performance of using the learning-based models within our VISR and compared it with the performances from conventional methods. Results show that the models enhanced the proposed robotic system with better navigation precision, faster response speed, and improved force measurement capabilities.

Mechanism design and force sensing of a novel cardiovascular interventional surgery robot

Robotic-assisted cardiovascular interventional surgery is an effective means to reduce the exposure of X-ray radiation to surgeons. However, some of the existing design structures cannot meet the surgical requirements for the coordinated delivery of multiple instruments or lack force sensing function. This article proposes a novel cardiovascular interventional surgery robot, which is in line with the operating habits of surgeons. Meanwhile, the force sensing function is integrated under the premise of satisfying the smaller size. Experimental results show that the proposed cardiovascular interventional surgery robot can quickly and accurately deliver multiple surgical instruments. Furthermore, it can accurately measure the force and torque experienced by the guidewire during the delivery process, which conforms to the derived dynamic model. The results demonstrate the effectiveness of force sensing and indicate the promise of the presented master-slave robotic system for cardiovascular interventional surgery.

Screening of factors influencing catheter rotation of a vascular interventional surgical robot using design of experiment approach

Over the past decades, Vascular Interventional Surgery Robots (VISR) have been developed to address the risks associated with X-rays used in minimally invasive vascular surgery procedures. Manipulation of over-the-wire catheters is necessary to perform complex surgery but requires high forces on the robot's end effector during rotational movements. The VISR under study mimics the physician's fingers by rolling the catheter between two planar surfaces to rotate it. In this study, an experimental set-up is used to replicate this grasping method, also used in other VISR [1, 2]. The parameters of the gripping surfaces are investigated to maximise the torque delivered to the catheter and minimise the forces required at the robot's end-effector. The implemented design of experiment (DOE) demonstrated that large and soft gripping surfaces could achieve this compromise. By adjusting these parameters, sufficient torque can be achieved on the catheter.

An Intravascular Catheter Bending Recognition Method for Interventional Surgical Robots

Robot-assisted interventional surgery can greatly reduce the radiation received by surgeons during the operation, but the lack of force detection and force feedback is still a risk in the operation which may harm the patient. In those robotic surgeries, the traditional force detection methods may have measurement losses and errors caused by mechanical transmission and cannot identify the direction of the force. In this paper, an interventional surgery robot system with a force detection device is designed and a new force detection method based on strain gauges is proposed to detect the force and infer the bending direction of the catheter in the vessel by using BP neural network. In addition, genetic algorithm is used to optimize the BP neural network, and the error between the calculated results and the actual results is reduced by 37%, which improves the accuracy of catheter bending recognition. Combining this new method with traditional force sensors not only reduces the error caused by the traditional mechanical transmission, but also can detect the bending direction of the catheter in the blood vessel, which greatly improves the safety of the operation.

A Bimodal Detection-Based Tremor Suppression System for Vascular Interventional Surgery Robots

Vascular interventional surgery (VIS) robots generally rely on faster and more accurate signal interaction system between the master side and slave side. During actual operations, unconscious and nonlinear tremors limit the accuracy and safety for VIS robot’s operation. To solve above issues, this article proposes a novel bimodal detection-based tremor suppression system to improve the accuracy of data interaction. More precisely, a bimodal tremor detection combined self-designed force sensitive resistor (FSR) and a linear encoder sensor is employed for radial and axial tremor detection, respectively. Tremor suppression method based on active restraint and passive modification is presented in this study, which can not only reduce the regular tremor but also effectively suppress the suddenly burst tremor. Experiments and performance analysis of the proposed method are evaluated from simulations and actual experimental results. Based on these evaluations, the tremor suppression method has obvious advantages for suppressing non-linear tremors and enhancing the timeliness of signal interaction, which the average computing time for tremor is 140 ms and average maximum amplitude moves to 2.47 mm. Moreover, we also discuss the issues for time delay and the transmission loss existed in actual experiments. Besides, this article has a potential impact on eliminating non-linear errors, improving the safety performance of operations for master–slave robotic system, and solving the crossing problem for time–frequency domain.

Design and analysis of positioning manipulator structure for vascular interventional surgery robot system

The positioning manipulator is an important part of the minimally invasive vascular interventional surgical robot system. In order to make the surgical robot system have high safety, convenience and accuracy, this paper designs a modular light weight manipulator as a positioning manipulator, which is used to realize the positioning and movement of the propulsion device. First, according to the requirements of the operation, the degree of freedom and configuration method of the manipulator are determined, and the configuration design and parameter selection of the manipulator are completed. Then, according to the structural characteristics of the articulated robot, the D-H parameter method and the inverse transformation method are used to analyze the kinematics of the manipulator and its working space are analyzed. On this basis, the manipulator is analyzed by finite element and verified by static simulation. Finally, the positioning manipulator can realize the function of dragging in its working space by hand to achieve the target pose.

Research on a Novel Vascular Interventional Surgery Robot and Control Method Based on Precise Delivery

In a vascular interventional surgery robot system, accurately pushing the guidewire into the patient-specific branch vessel is the core step of the entire operation, so it has become the focus of the master-slave co-control of the guidewire propulsion and manipulation mechanism. Some vascular interventional surgery robots have been used for delivery of the guidewire; however, problems such as the inability to reliably clamp the guidewire and the lack of accurate force feedback prevent doctors from using robots for accurate delivery. In addition, failure to disinfect surgical robots quickly and completely increases the risk of surgery. This article introduces a new type of master-slave vascular interventional robot with reliable clamping of the catheter/guidewire, accurate perception of the lead-in force of the guidewire for precise delivery and fast disinfection. In response to the problem of the nonlinear and uncertain disturbance of the catheter/guidewire resistance affecting the delivery mechanism, an adaptive sliding controller based on master-slave tracking is designed. Through experiments and analysis of the fuzzy sliding mode controller (FSMC) experimental platform, the results show that a vascular interventional robot control system with good tracking performance and strong robustness has been designed.

Machine learning-based operation skills assessment with vascular difficulty index for vascular intervention surgery.

An accurate assessment of surgical operation skills is essential for improving the vascular intervention surgical outcome and the performance of endovascular surgery robots. In existing studies, subjective and objective assessments of surgical operation skills use a variety of indicators, such as the operation speed and operation smoothness. However, the vascular conditions of particular patients have not been considered in the assessment, leading to deviations in the evaluation. Therefore, in this paper, an operation skills assessment method including the vascular difficulty level index for catheter insertion at the aortic arch in endovascular surgery is proposed. First, the model describing the difficulty of the vascular anatomical structure is established with characteristics of different aortic arch branches based on machine learning. Afterwards, the vascular difficulty level is set as an objective index combined with operating characteristics extracted from the operations performed by surgeons to evaluate the surgical operation skills at the aortic arch using machine learning. The accuracy of the assessment improves from 86.67 to 96.67% after inclusion of the vascular difficulty as an evaluation indicator to more objectively and accurately evaluate skills. The method described in this paper can be adopted to train novice surgeons in endovascular surgery, and for studies of vascular interventional surgery robots. Graphical abstract Operation skill assessment with vascular difficulty for vascular interventional surgery.

A Surgeon’s Operating Skills-Based Non-Interference Operation Detection Method for Novel Vascular Interventional Surgery Robot Systems

The vascular interventional surgery (VIS) is the most popular treatment for the cardiovascular and cerebrovascular diseases. Master-slave VIS robot is a promising technology to further improve the operation accuracy and surgical safety of both the patient and surgeon. The surgical outcome of robot assisted VIS highly depends on surgeon’s operating skills. However, current VIS robot systems affect the exerting of surgeon’s operating skills with different degrees due to the master manipulators with rigid-link structure or low detecting accuracy. To address this issue, a novel vascular interventional surgery robot based on surgeon’s operating skills is developed in this paper. A master manipulator is developed to contactlessly measure the surgeon’s operating motion. The surgeon operates the catheter with no limit, just as the operating manner in conventional VIS. It is enabled by measuring the catheter’s axial motion through tracking the edge of a series of markers with a macro camera, and by measuring the catheter’s rotational motion via a high-precise MEMS (Micro-Electro-Mechanic-System) gyroscope. Then, the developed master manipulator is integrated with a slave robot to construct the master-slave VIS robot system. Experimental results show that the detecting accuracy of the developed master manipulator are 0.71° and 0.104mm. Experimental results of surgical tasks implemented in EVE (endovascular evaluator) indicate that the developed robot system is superior to the system using a phantom as the master manipulator according to the metrics including operating time, path length, maximum speed and maximum accelerate.

A novel noncontact detection method of surgeon's operation for a master-slave endovascular surgery robot.

Master-slave endovascular interventional surgery (EIS) robots have brought revolutionary advantages to traditional EIS, such as avoiding X-ray radiation to the surgeon and improving surgical precision and safety. However, the master controllers of most of the current EIS robots always lead to bad human-machine interaction, because of the difference in nature between the rigid operating handle and the flexible medical catheter used in EIS. In this paper, a noncontact detection method is proposed, and a novel master controller is developed to realize real-time detection of surgeon's operation without interference to the surgeon. A medical catheter is used as the operating handle. It is enabled by using FAST corner detection algorithm and optical flow algorithm to track the corner points of the continuous markers on a designed sensing pipe. A mathematical model is established to calculate the axial and rotational motion of the sensing pipe according to the moving distance of the corner points in image coordinates. A master-slave EIS robot system is constructed by integrating the proposed master controller and a developed slave robot. Surgical task performance evaluation in an endovascular evaluator (EVE) is conducted, and the results indicate that the proposed detection method breaks through the axial measuring range limitation of the previous marker-based detection method. In addition, the rotational detection error is reduced by 92.5% compared with the previous laser-based detection method. The results also demonstrate the capability and efficiency of the proposed master controller to control the slave robot for surgical task implementation. Graphical abstract A novel master controller is developed to realize real-time noncontact detection of surgeon's operation without interference to the surgeon. The master controller is used to remotely control the slave robot to implement certain surgical tasks.

Innovative Design of Intervention Module for Vessel Intervention Surgery Robot Based on TRIZ Theory

Functional model of interventional surgery robot system is obtained based on the analysis of interventional surgery needs. Combining the original design results, functional models are further analyzed. An innovative design method of interventional surgery robot based on TRIZ theory is proposed to simply the mechanism and perfect function. The problem model is defined by using TRIZ method. System tailoring strategy based on functional model and invention principle based on conflict resolution theory are combined for solving the design problem. Then, the new structural scheme is given based on the above analyses. The synthesized structural scheme has been greatly simplified. Finally, the TRIZ theory is used to evaluate the innovative design scheme. It is concluded that the improvement of the new scheme relative to the original scheme follows the evolutionary mode of expansion and simplification of the technical system, and conforms to the evolutionary rule of the technical system.

Compensatory force measurement and multimodal force feedback for remote-controlled vascular interventional robot

Minimally invasive vascular interventional surgery is widely used and remote-controlled vascular interventional surgery robots (RVIRs) are being developed to reduce the occupational risk of the intervening physician in minimally invasive vascular interventional surgeries. Skilled surgeon performs surgeries mainly depending on the detection of collisions. Inaccurate force feedback will be difficult for surgeons to perform surgeries or even results in medical accidents. In addition, the surgeon cannot quickly and easily distinguish whether the proximal force exceeds the safety threshold of blood vessels or not, and thus it results in damage to the blood vessels. In this paper, we present a novel method comprising compensatory force measurement and multimodal force feedback (MFF). Calibration experiments and performance evaluation experiments were carried out. Experimental results demonstrated that the proposed method can measure the proximal force of catheter/guidewire accurately and assist surgeons to distinguish the change of proximal force more easily. This novel method is suitable for use in actual surgical operations.

Operation and force analysis of the guide wire in a minimally invasive vascular interventional surgery robot system

To develop a robot system for minimally invasive surgery is significant, however the existing minimally invasive surgery robots are not applicable in practical operations, due to their limited functioning and weaker perception. A novel wire feeder is proposed for minimally invasive vascular interventional surgery. It is used for assisting surgeons in delivering a guide wire, balloon and stenting into a specific lesion location. By contrasting those existing wire feeders, the motion methods for delivering and rotating the guide wire in blood vessel are described, and their mechanical realization is presented. A new resistant force detecting method is given in details. The change of the resistance force can help the operator feel the block or embolism existing in front of the guide wire. The driving torque for rotating the guide wire is developed at different positions. Using the CT reconstruction image and extracted vessel paths, the path equation of the blood vessel is obtained. Combining the shapes of the guide wire outside the blood vessel, the whole bending equation of the guide wire is obtained. That is a risk criterion in the delivering process. This process can make operations safer and man-machine interaction more reliable. A novel surgery robot for feeding guide wire is designed, and a risk criterion for the system is given.

Fuzzy Fusion of Forces Feedback in Vascular Interventional Surgery Robot System

In order to consummate the master-slave robot system used in vascular interventional procedures,a closed loop of force is rebuilt.Two micro force sensors are integrated with a catheter,which can measure those forces between the tip or side wall of the catheter and vascular walls respectively at the same time.Given that the master-slave mode is different from the traditional hands-on operation and that it is necessary to ensure the sustained effect of the valuable experience from surgeons,a two-input one-output model in fuzzy inference is adopted to accomplish the fusion of the two sensors’ data.By means of calibrating membership functions and establishing a table of fusion rules,experience is converted into numerical strategies about the force feedback,which not only improves the force reflection under low sampling rate,but also characterizes collisions accurately with different resolutions.It ensures the safety,applicability and efficiency of the robot system.