Study on real-time force feedback for a master–slave interventional surgical robotic system

Bone collision detection method for robot assisted fracture reduction based on vibration excitation

BACKGROUND AND OBJECTIVE

In the process of robotic fracture reduction, there is a risk of unintended collision of broken bones, which is not conducive to ensuring the safety of the reduction system. In order to solve this problem, this paper proposed a vibration-based collision detection method for fracture reduction process.

METHODS

Based on the two degree-of-freedom vibration response model, the factors affecting the respond of the vibration, including the excitation voltage, the clamping length at the proximal and distal ends, the mass and tensile force of the soft tissue, were obtained. The effects of these factors on the vibration transfer performance of broken bones and soft tissue were investigated by single factor experiments.

RESULTS

The results showed that, in terms of peak value, the increase of excitation voltage would make the vibration amplitude increase linearly, and the increase of soft tissue mass and tension increased the vibration transmission capacity of soft tissue in the frequency range of 500-1000 Hz. In terms of peak frequency, the clamping length at the distal end had the greatest influence, which reached 74 Hz, followed by 45 Hz at the proximal end. While the influence of other factors was little. According to single factor experiments, the excitation frequency in the verification experiments was determined as 677 Hz. Under the vibration interference with the acceleration amplitude of 1.2 G, this method achieved correct detection.

CONCLUSION

This research developed a broken bone collision detection method based on vibration excitation. The method can correctly detect the collision of broken bones with strong anti-interference ability. It is of great significance to improve the safety of fracture reduction process.

Development of a Force Sensor for a Neuroendovascular Intervention Support Robot System

Neuroendovascular catheterization using fluoroscopy poses the problem to operators and staffs of cumulative radiation exposure. To solve this problem, we are developing a remote-controlled master-slave robot. Because a wire-like elongated treatment device is inserted into a blood vessel using a catheter, the robot requires a sensor to detect the insertion force of the wire. The proposed sensor is integrated into a robot installed in an X-ray fluoroscopy room that is remotely controlled from another room. The features of this sensor include measurement of the insertion force with sufficient accuracy, simple wire attachment, and an inexpensive disposable sensor head, rendering it very suitable for practical application. In this paper, we report on these features, as well as the results of a practical test of the sensor using a cerebrovascular model.

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.

Bone collision detection method for robot assisted fracture reduction based on force curve slope

BACKGROUND AND OBJECTIVE

The application of robot technology in fracture reduction ensures the minimal invasiveness and accurate operation process. Most of the existing robot assisted fracture reduction systems don't have the function of bone collision detection, which is very important for system safety. In view of the deficiencies in the research of this field, a broken bone collision detection method based on the slope ratio of force curve was proposed in this paper, which could realize the real-time detection.

METHODS

In order to analyze the factors influencing the slope of force curve, a collision mechanical model based on three-element viscoelastic model was established. The effects of four factors on the slope ratio of the force curve were studied based on the mechanical model. The proposed collision detection model was analyzed in detail. By drawing slope ratio curves under various experimental conditions, the universality of the collision detection model was proved; by comparative simulation, the differences between the slope ratio curves before and after optimization were analyzed. The factors that affect the performance of the detection model were also analyzed.

RESULTS

The results of collision experiments show that the increase of moving speed of distal bone and soft tissue mass reduces the slope ratio, while the increase of collision angle increases the slope ratio. In the verification experiment, the minimum main peak of KR_opt curve is 14.16 and the maximum is 220.7, the maximum interference value before the peak is 6.1. When the detection threshold is 10, the model can detect the collision state of the broken bone. It is also proved that after optimization, the model can effectively filter out invalid waveforms and reduce the occurrence of false detections. When a=5 and b=40, the detection model has sufficient stability and a low detection time delay.

CONCLUSION

This research developed a broken bone collision detection method based on the slope ratio of the force curve. After optimization, the method has good adaptability under a variety of experimental conditions. The collision of broken bones can be judged by setting an appropriate detection threshold. The application of this method in the robot fracture reduction system will improve the safety of the system.

Animal Experiment of a Novel Neurointerventional Surgical Robotic System with Master-Slave Mode

In order to inspect and improve the system performance of the neuro-interventional surgical robot and its effectiveness and safety in clinical applications, we conducted ten animal experiments using this robotic system. Cerebral angiography was performed on ten experimental animals, and various mechanical performance indicators, operating time, X-ray radiation dosage to the experimental animals and the experimenter, and arterial damage in the experimental animals were recorded when the robotic system completed cerebral angiography. The results show that the robotic system can successfully complete the cerebral angiography surgery, and the mechanical performance is up to standard. The operating time is almost the same as the physician's operating time. And the mean X-ray radiation dosage received by the experimental animals and experimenter was 0.893 Gy and 0.0859 mSv, respectively. There were no complications associated with damage to the vascular endothelium. The robotic system can basically complete the relevant assessment indicators, and its system performance, effectiveness, and safety in clinical applications meet the standards, basically meeting the requirements of clinical applications of neurointerventional surgery.

Development of a microsurgery-assisted robot for high-precision thread traction and tension control, and confirmation of its applicability

Background

Microsurgery requires high skills for suturing using fragile threads, often within narrow surgical fields. Precise tension is required for good healing and to avoid the risk of thread breakage.

Methods

To meet the demands, we developed a novel assist robot utilizing high‐precision sensorless haptic technology. The robot adopts a cable‐driven mechanism to maintain a distance from the surgical area and enhances compatibility with surgical equipment such as microscopes. The robot performance was verified through in vitro and in vivo experiments using a rat model.

Results

The realization of precise tension control was confirmed in both experiments. In particular, in the in vivo experiments, the developed robot succeeded to produce a knot with an accurate tension of 0.66% error.

Conclusions

The developed robot can realize to control traction force precisely. This technology might open up the window for a full assist robot for microsurgery with haptic feeling.

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 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.

A vascular interventional surgical robot based on surgeon's operating skills

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.

Haptic Telerobotic Cardiovascular Intervention: A Review of Approaches, Methods, and Future Perspectives

Cardiac diseases are recognized as the leading cause of mortality, hospitalization, and medical prescription globally. The gold standard for the treatment of coronary artery stenosis is the percutaneous cardiac intervention that is performed under live X-ray imaging. Substantial clinical evidence shows that the surgeon and staff are prone to serious health problems due to X-ray exposure and occupational hazards. Telerobotic vascular intervention systems with a master-slave architecture reduced the X-ray exposure and enhanced the clinical outcomes; however, the loss of haptic feedback during surgery has been the main limitation of such systems. This paper is a review of the state of the art for haptic telerobotic cardiovascular interventions. A survey on the literature published between 2000 and 2019 was performed. Results of the survey were screened based on their relevance to this paper. Also, the leading research disciplines were identified based on the results of the survey. Furthermore, different approaches for sensor-based and model-based haptic telerobotic cardiovascular intervention, haptic rendering and actuation, and the pertinent methods were critically reviewed and compared. In the end, the current limitations of the state of the art, unexplored research areas as well as the future perspective of the research on this technology were laid out.

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.