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Magnetically manipulated interventional robotic systems offer outstanding advantages for improving vascular interventions, including minimizing radiation exposure to physicians and increasing the controllability of magnetic interventional devices in hard‐to‐reach vessels. However, automatic control of magnetic guidewires (MGs) is still challenging in terms of modeling of guidewires and trajectory planning. Herein, a magnetically controlled guidewire robotic system (MCGRS) with steering and propulsion capabilities is proposed based on adequate modeling and trajectory planning methods. The steering kinematics of MG is first modeled by constant curvature theory. Then, a continuum mechanics model is built to predict the deformation of the magnetic tip by combining the dipole model and the Cosserat‐rod model. Moreover, a trajectory planning algorithm is developed to navigate the MG through vessels. Furthermore, trajectory following experiments within three vascular phantoms confirm that the proposed model and algorithm are reliable and capable of navigating the MG through the desired trajectory. Finally, two extra navigation experiments are implemented in 3D vascular phantom, which show that the MCGRS can be remotely controlled to manipulate the MG to actively steer and reach the target site. The system and methods will build the foundation for automatic control of MG and help to improve the autonomy. [ABSTRACT FROM AUTHOR]

Abstract Background Minimally invasive vascular intervention (MIVI) is a powerful technique for the treatment of cardiovascular diseases, such as abdominal aortic aneurysm (AAA), thoracic aortic aneurysm (TAA) and aortic dissection (AD). Navigation of traditional MIVI surgery mainly relies only on 2D digital subtraction angiography (DSA) images, which is hard to observe the 3D morphology of blood vessels and position the interventional instruments. The multi-mode information fusion navigation system (MIFNS) proposed in this paper combines preoperative CT images and intraoperative DSA images together to increase the visualization information during operations. Results The main functions of MIFNS were evaluated by real clinical data and a vascular model. The registration accuracy of preoperative CTA images and intraoperative DSA images were less than 1 mm. The positioning accuracy of surgical instruments was quantitatively assessed using a vascular model and was also less than 1 mm. Real clinical data used to assess the navigation results of MIFNS on AAA, TAA and AD. Conclusions A comprehensive and effective navigation system was developed to facilitate the operation of surgeon during MIVI. The registration accuracy and positioning accuracy of the proposed navigation system were both less than 1 mm, which met the accuracy requirements of robot assisted MIVI.

Magnetically manipulated interventional robotic systems offer outstanding advantages for improving vascular interventions, including minimizing radiation exposure to physicians and increasing the controllability of magnetic interventional devices in hard‐to‐reach vessels. However, automatic control of magnetic guidewires (MGs) is still challenging in terms of modeling of guidewires and trajectory planning. Herein, a magnetically controlled guidewire robotic system (MCGRS) with steering and propulsion capabilities is proposed based on adequate modeling and trajectory planning methods. The steering kinematics of MG is first modeled by constant curvature theory. Then, a continuum mechanics model is built to predict the deformation of the magnetic tip by combining the dipole model and the Cosserat‐rod model. Moreover, a trajectory planning algorithm is developed to navigate the MG through vessels. Furthermore, trajectory following experiments within three vascular phantoms confirm that the proposed model and algorithm are reliable and capable of navigating the MG through the desired trajectory. Finally, two extra navigation experiments are implemented in 3D vascular phantom, which show that the MCGRS can be remotely controlled to manipulate the MG to actively steer and reach the target site. The system and methods will build the foundation for automatic control of MG and help to improve the autonomy.

Robot-assisted systems for vascular interventional surgery (VIS) have the advantages of high precision and an improved operating environment for the surgeon. However, the current robot-assisted systems cannot completely replace human beings in controlling interventional devices—for example, rapid guidewire/catheter replacement and force feedback. In the face of these challenges, the robot-assisted system presented in this article can better solve the above problems. The experiments for the guidewire and catheter were designed and performed separately based on the developed robot-assisted system. The experimental results show that the participants can use the system to manipulate the guidewire and catheter to reach the designated blood vessel position. Based on the experiments for the catheter, for the first time, the reciprocating manipulation method with visual-based force feedback (VFF) was used for experimental evaluation. The experimental results show that this method can effectively avoid the buckling phenomenon of the catheter; the VFF plays a vital role in improving the safety of the operation and provides an operational assessment of VIS safety. In addition, this article puts forward the evaluation index for maximum pull force (MPLF) and force fluctuation, which provides an essential reference for enriching the evaluation of VIS technical skills. [ABSTRACT FROM AUTHOR]

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Interventional surgery robots are essential in cardiovascular surgery as remote medical devices. By performing remote surgery, surgeons can reduce surgical fatigue and after-effects from heavy surgical instruments and radiation, ensuring that cardiovascular surgery is performed in a safe and reliable manner. To enhance stability during interventional procedures and reduce the impact of surgical risk due to factors where the robotic guidewire section from the end is vulnerable to mechanical jitter or blockage by blood flow, lipids, and thrombus inside the vessel, a new control method is proposed. The active disturbance rejection controller (ADRC) combined with intelligence algorithms is used to improve the performance of the controller by introducing the fuzzy inference algorithm and RBF neural network algorithm to self-adjust the parameters of the controller so that it has a greater ability to compensate for the disturbance factors appearing in the system. In numerical simulation experiments, the advantages and disadvantages of the ADRC combined with intelligence algorithms and the control performance of the conventional control strategy are analyzed in terms of the following: disturbance suppression performance and flexibility performance, respectively. Finally, different types of working conditions have been designed in the experimental platform to simulate the operation flow of in vivo vascular surgery. Experimental results show that the controller proposed in this paper meets the high accuracy, fast response, and low deviation required by interventional vascular surgery robots in complex surgical environments and can provide a more reliable guarantee for the stability of interventional surgery robots. [ABSTRACT FROM AUTHOR]

Background: Minimally invasive vascular intervention (MIVI) is a powerful technique for the treatment of cardiovascular diseases, such as abdominal aortic aneurysm (AAA), thoracic aortic aneurysm (TAA) and aortic dissection (AD). Navigation of traditional MIVI surgery mainly relies only on 2D digital subtraction angiography (DSA) images, which is hard to observe the 3D morphology of blood vessels and position the interventional instruments. The multi-mode information fusion navigation system (MIFNS) proposed in this paper combines preoperative CT images and intraoperative DSA images together to increase the visualization information during operations. Results: The main functions of MIFNS were evaluated by real clinical data and a vascular model. The registration accuracy of preoperative CTA images and intraoperative DSA images were less than 1 mm. The positioning accuracy of surgical instruments was quantitatively assessed using a vascular model and was also less than 1 mm. Real clinical data used to assess the navigation results of MIFNS on AAA, TAA and AD. Conclusions: A comprehensive and effective navigation system was developed to facilitate the operation of surgeon during MIVI. The registration accuracy and positioning accuracy of the proposed navigation system were both less than 1 mm, which met the accuracy requirements of robot assisted MIVI. [ABSTRACT FROM AUTHOR]

Robot-assisted systems for vascular interventional surgery (VIS) have the advantages of high precision and an improved operating environment for the surgeon. However, the current robot-assisted systems cannot completely replace human beings in controlling interventional devices—for example, rapid guidewire/catheter replacement and force feedback. In the face of these challenges, the robot-assisted system presented in this article can better solve the above problems. The experiments for the guidewire and catheter were designed and performed separately based on the developed robot-assisted system. The experimental results show that the participants can use the system to manipulate the guidewire and catheter to reach the designated blood vessel position. Based on the experiments for the catheter, for the first time, the reciprocating manipulation method with visual-based force feedback (VFF) was used for experimental evaluation. The experimental results show that this method can effectively avoid the buckling phenomenon of the catheter; the VFF plays a vital role in improving the safety of the operation and provides an operational assessment of VIS safety. In addition, this article puts forward the evaluation index for maximum pull force (MPLF) and force fluctuation, which provides an essential reference for enriching the evaluation of VIS technical skills.

In robot-assisted vascular interventional surg- ery (VIS), surgeons often need to operate outside the operating room to avoid exposure to X-ray. However, it greatly changes the operating ways of surgeons, which affects judgment and operation safety. In this paper, a novel VIS robot system was developed to predict guidewire insertion states and operate collaboratively. To assist the surgeons in perceiving the insertion state, an insertion multi-states prediction model based on softmax logistic regression was proposed. Combined with the prediction model, a human-machine collaborative control strategy was designed, which allows surgeons to perceive the insertion states based on not only the force feedback constructed by the master side but also the prediction results from the slave side. Moreover, a human-machine trust evaluation model and a master-slave collaborative mapping model were proposed for improving safety and efficiency of surgery. To verify the effectiveness of these models, the evaluation experiments in the blood vessel model were carried out. It was indicated by the experiment results that the guidewire insertion states can be predicted by the prediction model in different environments, and the overall accuracy is 93%. The master-slave mapping ratio can be adjusted by the collaborative control strategy automatically to adapt to different surgical conditions. The experimental results showed the usability of the robot-assisted VIS system with the novel force-based perception method. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVDs) are the deadliest diseases worldwide. Master-slave robotic systems have been widely used in vascular interventional surgery with the benefit of high safety, efficient operation, and procedural facilitation. This paper introduces a remote-controlled vascular interventional robot (RVIR) that aims to enable surgeons to perform complex vascular interventions reliably and accurately under a magnetic resonance imaging (MRI) environment. The slave robot includes a guidewire manipulator (GM) and catheter manipulator (CM) that are mainly composed of a hollow driving mechanism and a linear motion platform. The hollow driving mechanism is based on a traveling wave-type hollow ultrasonic motor (HUM) which has high positional precision, fast response, and magnetic interference resistance and realizes the cooperation of the guidewire and catheter by omitting the redundant transmission mechanism and maintaining good coaxiality. The HUM stator, the core part of the RVIR, is optimized by an adaptive genetic algorithm for better quality and greater amplitude of traveling waves, which are beneficial to the drive efficiency and precision. The robot system features great cooperating performance, small hysteresis, and high kinematic accuracy and has been experimentally verified for its capability to precisely manipulate the guidewire and catheter. [ABSTRACT FROM AUTHOR]

In vascular interventional surgery (VIS), the doctors often need to be exposed to X-ray radiation for a long time, operate surgical instruments (Ex. Guidewires and catheters) to perform the operation, which is difficult to ensure the health of surgeons and the safety of operation. In addition, the force between the blood vessel wall and the surgical instrument is complex and variable, the existence of the external disturbance forces easily affects the judgment of the doctors. In this paper, to ensure the health and reduce the fatigue of the doctors, a novel tactile sensing robot-assisted system for VIS was developed to assist the surgeons to complete the operation. Then, the forces between the blood vessel and the surgical instrument during the surgery were analyzed. Besides, a self-developed force sensor was used to confirm the collision force between the tip of the catheter and the blood vessel wall. Finally, combining the haptic force feedback of the system and the developed force sensor, a series of experiments in “Vitro” were completed, and it was indicated by the experiment results that the accuracy of the force feedback can be improved by using the analysis method proposed in this paper, the collision force between the catheter tip and the blood vessel environment can be confirmed by the self-developed force sensor. Based on the results, the developed robot-assisted system for VIS has high safety. [ABSTRACT FROM AUTHOR]

In vascular interventional surgery, experienced physicians rely on proximal force sensing to detect the collision and reduce vascular injury caused by surgical tools. However, in robot-assisted tele-interventional surgery (RATIS), providing high-precision force feedback to physician is still a main challenge. In this paper, a haptic robot-assisted catheter operating system with a novel spring-based haptic force interface was developed. With a closed loop force adjustment system, the haptic force interface can provide accuracy force feedback. Moreover, a collision protection function with a proximal-force-based collision detection algorithm was proposed to improve surgical safety. In case of no collision, transparency of the teleoperated system is realized; in case of collision, the provided haptic force will be amplified. The results demonstrated the usability of the developed haptic robot-assisted catheter operating system with collision protection function. [ABSTRACT FROM AUTHOR]

The challenge of vascular interventional surgery is that surgeons require to be exposed to X-ray for a long time, operating guidewires and catheters to complete the treatment. To reduce the burden of the surgeons, it is of great significance to develop a tactile sensing robot-assisted system for vascular interventional surgery. Therefore, a slave manipulator with the function of collaborative operating guidewires and catheters was developed to replace doctors to perform the surgery in the operating room. In addition, a master manipulator based on magnetorheological fluids was located on the master side, and the haptic force feedback of the system was realized by generating the tactile force acting on the doctor’s hand. To verify the proposed system, a series of experiments were carried out, the results of experiments in “Vitro” indicated that the proposed system has good performance in collaborative operating and can accurately deliver a guidewire and a catheter to the target position. The maximum tracking error of the axial motion was less than 2 mm, and the maximum tracking error of the radial motion was less than 2 degrees, which is acceptable. And under the guidance of the force feedback, the safety of the system was obviously higher than that of without force feedback, after the experiment was completed by 5 participants, the safety increased by 4.32% on average. So, we can get the results that our system is feasible and effective. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVDs) are the deadliest diseases worldwide. Master-slave robotic systems have been widely used in vascular interventional surgery with the benefit of high safety, efficient operation, and procedural facilitation. This paper introduces a remote-controlled vascular interventional robot (RVIR) that aims to enable surgeons to perform complex vascular interventions reliably and accurately under a magnetic resonance imaging (MRI) environment. The slave robot includes a guidewire manipulator (GM) and catheter manipulator (CM) that are mainly composed of a hollow driving mechanism and a linear motion platform. The hollow driving mechanism is based on a traveling wave-type hollow ultrasonic motor (HUM) which has high positional precision, fast response, and magnetic interference resistance and realizes the cooperation of the guidewire and catheter by omitting the redundant transmission mechanism and maintaining good coaxiality. The HUM stator, the core part of the RVIR, is optimized by an adaptive genetic algorithm for better quality and greater amplitude of traveling waves, which are beneficial to the drive efficiency and precision. The robot system features great cooperating performance, small hysteresis, and high kinematic accuracy and has been experimentally verified for its capability to precisely manipulate the guidewire and catheter.

• An interaction force model between guidewires and blood vessels is constructed. • The force model provides predicted corresponding force value impacted on blood vessels. • Interaction force model enables operators to optimize the actual intervention strategy. • Force model prediction prevents too much compression collisions that causing vascular damage. • Optimized intervention strategy decreased the force on blood vessels approximately 21.97 %. A profound investigation of the interaction mechanics between blood vessels and guidewires is necessary to achieve safe intervention. An interactive force model between guidewires and blood vessels is established based on cardiovascular fluid dynamics theory and contact mechanics, considering two intervention phases (straight intervention and contact intervention at a corner named "J-vessel"). The contributing factors of the force model, including intervention conditions, guidewire characteristics, and intravascular environment, are analyzed. A series of experiments were performed to validate the availability of the interactive force model and explore the effects of influential factors on intervention force. The intervention force data were collected using a 2-DOF mechanical testing system instrumented with a force sensor. The guidewire diameter and material were found to significantly impact the intervention force. Additionally, the intervention force was influenced by factors such as blood viscosity, blood vessel wall thickness, blood flow velocity, as well as the interventional velocity and interventional mode. The experiment of the intervention in a coronary artery physical vascular model confirms the practicality validation of the predicted force model and can provide an optimized interventional strategy for vascular interventional surgery. The enhanced intervention strategy has resulted in a considerable reduction of approximately 21.97 % in the force exerted on blood vessels, effectively minimizing the potential for complications associated with the interventional surgery. [Display omitted] [ABSTRACT FROM AUTHOR]

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.

In vascular interventional surgery, surgeons operate guidewires and catheters to diagnose and treat patients with the assistance of the digital subtraction angiography (DSA). Therefore, the surgeon will be exposed to X-rays for extended periods. To protect the surgeon, the development of a robot-assisted surgical system is of great significance. The displacement tracking accuracy is the most important issue to be considered in the development of the system. In this study, the active disturbance rejection control (ADRC) method is applied to guarantee displacement tracking accuracy. First, the core contents of the proportional–integral–derivative (PID) and ADRC methods are analyzed. Second, comparative evaluation experiments for incremental PID and ADRC methods are presented. The results show that the ADRC method has better performance of than that of the incremental PID method. Finally, the calibration experiments for the ADRC control method are implemented using the master–slave robotic system. These experiments demonstrate that the maximum tracking error is 0.87 mm using the ADRC method, effectively guaranteeing surgical safety.

Interventional surgery is widely used in the treatment of cardiovascular and cerebrovascular diseases, and the development of surgical robots can greatly reduce the fatigue and radiation risks brought to surgeons during surgery. In this paper, we present a novel interventional surgical robot which allows surgeons to fully use their operating skills during remote control. Fuzzy control theory is used to guarantee control precision during the master-slave operation. The safety force feedback control is designed based on the catheter and guidewire spring model, and the force-position control is designed to decrease the potential damage due to the control delay. This study first evaluates the force-position control strategy using a vascular model experiment, and then an in vivo experiment is used to evaluate the precision of the surgical robot controlling the catheter and guidewire to the designated position. The in vivo experiment results and surgeon's feedback demonstrate that the proposed surgical robot is able to perform complex remote surgery in clinical application. Graphical abstract Surgeons perform remote interventional animal surgery using interventional surgical robots. [ABSTRACT FROM AUTHOR]

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.

This article investigates the relationship of rotation angle of two ends of elastic guidewires, and motion method of guidewires and catheters in bifurcated blood vessels. The relationship of rotation angles of the two ends of the guidewire has first been studied by mathematical reasoning, indicating that the rotation angle of the front end of guidewire can be precisely described by that of the rear end. In order to satisfy the requirements of different vascular interventional surgeries, we further investigated a general model of bifurcated human blood vessels. Based on this model, a new motion method, which ensures the guidewire and catheter move cooperatively along center lines of blood vessels to the final target point, has been introduced. Rotation angles of the guidewire in this model were then analyzed. By experiments to verify the functional relationship between rotation angles of two ends of guidewire, the motion method and algorithm of guidewire and catheter are correct. Our study provides references for future studies in fully automated vascular interventional surgeries. [ABSTRACT FROM AUTHOR]

Soft robotics-based teleoperated robotic catheter systems hold great promise for improving the safety and efficacy of vascular interventional surgery (VIS). Despite advances, current robotic catheter systems actuated via cables have low stability, high force loss, lack of force sensing, and low stability when working against the dynamic cardiothoracic environment, all of which significantly reduce their effectiveness in clinical settings. Therefore, it is essential to equip the robotic catheters with a stabilizing mechanism (SM), a real-time force sensor, and the ability to expand the workspace without moving its body. This work introduces a new concept of a miniaturized soft robotic catheter (MSRC) for the VIS. The system consists of a soft manipulator for navigation and bending motion, a variable stiffness stabilizing mechanism (VSSM), and a soft force sensor for monitoring tool-tissue contact. By employing soft hydraulic filament artificial muscles (HFAMs), the flexible manipulator has an omnidirectional and extendable workspace and can generate a force of 0.375 N, which is monitored by a new HFAM-based sensor with a high sensitivity of about 10.7 KPa/N. The new VSSM can be deployed as a lantern form with a wide diameter range from 6 mm to 25 mm, potentially enhancing the catheter tip's stability at various blood vessels (e.g., the inferior vena cava IVC) to perform VIS. The VSSM has a controllable deploying force and is capable of withstanding highly compressed forces with little deflection. The system feasibility to perform cardiac ablation is demonstrated with a simulated heart's right atrium (RA), potentially offering a reliable tool for the treatment of atrial fibrillation (AF). The design, modelling, and fabrication of the device are also presented and followed by experimental characterizations, and ex-vivo tests. [Display omitted] • A novel soft robotic catheter with integrated bending and extending, stabilizing, and sensing ability is developed. • An omnidirectional manipulator with extendable workspace for bending and extending motion is fabricated and characterized. • A stabilizing mechanism with a unique characteristic of variable stiffness is proposed to use for stabilizing the catheter. • A new and low-cost soft force sensor with high sensitivity for monitoring tool-tissue contacts is proposed. • Ex-vivo experiments of the system performing ablation in the heart's right atrium (RA) are conducted. [ABSTRACT FROM AUTHOR]

Background: The emergence and development of robot assistant interventional vascular surgery technologies have benefited many patients with cardiovascular or cerebrovascular diseases. Due to the absence of effective training measures, these new advanced technologies have not been fully utilized and only few experienced surgeons can perform such complicated surgeries so far. In order to solve such problems, virtual reality based vascular interventional surgery training system, a promising way to train young surgeons or assist experienced surgeons to perform surgery, has been widely studied.Methods: In this paper, we mainly conduct a thorough study on both reliable deformation and high real-time performance of an interactive surgery training system. An efficient hybrid geometric blood vessel model which handles the collision detection query and vascular deformation calculation separately is employed to enhance the real-time performance of our surgery training system. In addition, a position-based dynamic approach with volume conservation constraint is used to improve the vascular deformation result. Finally, a hash table based spatial adaptive acceleration algorithm which makes the training system much more efficient and reliable is described.Results: Several necessary experiments are conducted to validate the vascular deformation scheme presented in this paper. From the results we can see that the position-based dynamic modeling method with volume conservation constraint can prevent the vascular deformation from the issue of penetration. In addition, the deformation calculation with spatial acceleration algorithm has enhanced the real-time performance significantly.Conclusion: The corresponding experimental results indicate that both the hybrid geometric blood vessel model and the hash table based spatial adaptive acceleration algorithm can enhance the performance of our surgery training system greatly without losing the deformation accuracy. [ABSTRACT FROM AUTHOR]

In vascular interventional surgery, surgeons operate guidewires and catheters to diagnose and treat patients with the assistance of the digital subtraction angiography (DSA). Therefore, the surgeon will be exposed to X-rays for extended periods. To protect the surgeon, the development of a robot-assisted surgical system is of great significance. The displacement tracking accuracy is the most important issue to be considered in the development of the system. In this study, the active disturbance rejection control (ADRC) method is applied to guarantee displacement tracking accuracy. First, the core contents of the proportional–integral–derivative (PID) and ADRC methods are analyzed. Second, comparative evaluation experiments for incremental PID and ADRC methods are presented. The results show that the ADRC method has better performance of than that of the incremental PID method. Finally, the calibration experiments for the ADRC control method are implemented using the master–slave robotic system. These experiments demonstrate that the maximum tracking error is 0.87 mm using the ADRC method, effectively guaranteeing surgical safety. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]