Design, Development, and Testing of an Automated Laparoscopic Grasper with 3-D Force Measurement Capability

Enhanced grip force estimation in robotic surgery: A sparrow search algorithm-optimized backpropagation neural network approach

The absence of an effective gripping force feedback mechanism in minimally invasive surgical robot systems impedes physicians' ability to accurately perceive the force between surgical instruments and human tissues during surgery, thereby increasing surgical risks. To address the challenge of integrating force sensors on minimally invasive surgical tools in existing systems, a clamping force prediction method based on mechanical clamp blade motion parameters is proposed. The interrelation between clamping force, displacement, compression speed, and the contact area of the clamp blade indenter was analyzed through compression experiments conducted on isolated pig kidney tissue. Subsequently, a prediction model was developed using a backpropagation (BP) neural network optimized by the Sparrow Search Algorithm (SSA). This model enables real-time prediction of clamping force, facilitating more accurate estimation of forces between instruments and tissues during surgery. The results indicate that the SSA-optimized model outperforms traditional BP networks and genetic algorithm-optimized (GA) BP models in terms of both accuracy and convergence speed. This study not only provides technical support for enhancing surgical safety and efficiency, but also offers a novel research direction for the design of force feedback systems in minimally invasive surgical robots in the future.

Measuring interaction forces in surgical telemanipulation using conventional instruments

Minimally invasive surgery (MIS) has been an essential tool in the surgical sector for many years due to its crucial advantages compared to open surgery. To overcome remaining limitations, teleoperated MIS experienced a strong emergence. However, the widespread usage of such systems is hindered by the enormous financial hurdle. The use of standard components and conventional tools for teleoperated MIS can facilitate integration into existing hospital workflows and can be a cost-efficient and versatile approach for research purposes. To compensate for the lack of haptic feedback, some teleoperation setups inherit a sensor system allowing them to record interaction forces and display them at the user interface. In research and in commercially available systems, different positions for the sensor can be found. In this paper, mechanical interfaces for the guidance and actuation of non-wristed and wristed standard instruments are presented. Furthermore, a method for the extracorporeal measurement of interaction forces is presented, characterized, and discussed. The overall mean relative error of the magnitude of the interaction force is 9.4%, while the overall mean absolute error of the force vector is 14.4 $^{\circ }$ , both below the respective human differential perception threshold. The presented measurement method is a simple, yet sufficiently accurate approach to measure interaction forces in surgical telemanipulation.

Tactile Sensing for Minimally Invasive Surgery: Conventional Methods and Potential Emerging Tactile Technologies

As opposed to open surgery procedures, minimally invasive surgery (MIS) utilizes small skin incisions to insert a camera and surgical instruments. MIS has numerous advantages such as reduced postoperative pain, shorter hospital stay, faster recovery time, and reduced learning curve for surgical trainees. MIS comprises surgical approaches, including laparoscopic surgery, endoscopic surgery, and robotic-assisted surgery. Despite the advantages that MIS provides to patients and surgeons, it remains limited by the lost sense of touch due to the indirect contact with tissues under operation, especially in robotic-assisted surgery. Surgeons, without haptic feedback, could unintentionally apply excessive forces that may cause tissue damage. Therefore, incorporating tactile sensation into MIS tools has become an interesting research topic. Designing, fabricating, and integrating force sensors onto different locations on the surgical tools are currently under development by several companies and research groups. In this context, electrical force sensing modality, including piezoelectric, resistive, and capacitive sensors, is the most conventionally considered approach to measure the grasping force, manipulation force, torque, and tissue compliance. For instance, piezoelectric sensors exhibit high sensitivity and accuracy, but the drawbacks of thermal sensitivity and the inability to detect static loads constrain their adoption in MIS tools. Optical-based tactile sensing is another conventional approach that facilitates electrically passive force sensing compatible with magnetic resonance imaging. Estimations of applied loadings are calculated from the induced changes in the intensity, wavelength, or phase of light transmitted through optical fibers. Nonetheless, new emerging technologies are also evoking a high potential of contributions to the field of smart surgical tools. The recent development of flexible, highly sensitive tactile microfluidic-based sensors has become an emerging field in tactile sensing, which contributed to wearable electronics and smart-skin applications. Another emerging technology is imaging-based tactile sensing that achieved superior multi-axial force measurements by implementing image sensors with high pixel densities and frame rates to track visual changes on a sensing surface. This article aims to review the literature on MIS tactile sensing technologies in terms of working principles, design requirements, and specifications. Moreover, this work highlights and discusses the promising potential of a few emerging technologies towards establishing low-cost, high-performance MIS force sensing.

Pneumatically driven surgical forceps displaying a magnified grasping torque

BACKGROUND

Sensing the grasping force and displaying the force for the operator are important for safe operation in robot-assisted surgery. Although robotic forceps that senses the force by force sensors or driving torque of electric motors is proposed, the force sensors and the motors have some problems such as increase in weight and difficulty of the sterilization.

METHOD

We developed a pneumatically driven robotic forceps that estimates the grasping torque and display the magnified torque for the operator. The robotic forceps has a master device and a slave robot, and they are integrated. In the slave side, the grasping torque is estimated by the pressure change in the pneumatic cylinder. A pneumatic bellows display the torque through a linkage.

RESULTS

We confirmed that the slave robot follows the motion of the master, and the grasping torque is estimated in the accuracy of 7 mNm and is magnified and displayed for the operator.

CONCLUSIONS

The pneumatically driven robotic forceps has the capability in the estimation of the grasping torque and display of the torque. Regarding future work, the usability and fatigues of the surgeons must be evaluated.

Three-dimensional nonlinear force-sensing method based on double microgrippers with E-type vertical elastomer for minimally invasive robotic surgery

This paper presents a new type of forceps that consist of two microgrippers with the capability of direct force sensing, which enables grasping and manipulating forces at the tip of surgical instrument for minimally invasive robotic surgery. For the prototype design of the forceps, a double E-type vertical elastomer with four strain beams is presented, whose force-sensing principle is expounded. Thus, the forceps with the elastomer can be considered a compliant component, which provides tiny displacements that allow large strain, and the overall diameter is 10 mm. The sizes of the elastomer and forceps are successively determined by analyzing the relationship of several parameters and strain. Then, the linearity analysis of strain beams determines the positions to apply gauges for sensing. The two-dimensional force decoupling models for a single microgripper are proposed based on piecewise analytical polynomials of the strain difference and employed to develop a new three-dimensional force nonlinear decoupling algorithm based on double microgrippers, which realizes single-axial grasping and three-axial pulling forces. Finally, the required force-sensing performance of the proposed method is successfully verified in theory using finite-element simulations.

Gaussian Process Regression for Sensorless Grip Force Estimation of Cable Driven Elongated Surgical Instruments

Haptic feedback is a critical but a clinically missing component in robotic Minimally Invasive Surgeries. This paper proposes a Gaussian Process Regression(GPR) based scheme to address the gripping force estimation problem for clinically commonly used elongated cable-driven surgical instruments. Based on the cable-driven mechanism property studies and surgical robotic system properties, four different Gaussian Process Regression filters were designed and analyzed, including: one GPR filter with 2-dimensional inputs, one GPR filter with 3-dimensional inputs, one GPR Unscented Kalman Filter (UKF) with 2-dimensional inputs, and one GPR UKF with 3-dimensional inputs. The four proposed methods were compared with the dynamic model based UKF filter on a 10mm gripper on the Raven-II surgical robot platform. The experimental results demonstrated that the four proposed methods outperformed the dynamic model based method on precision and reliability without parameter tuning. And surprisingly, among the four methods, the simplest GPR Filter with 2-dimensional inputs has the best performance.

Development and testing of a grasper for NOTES powered by variable stiffness pneumatic actuation

BACKGROUND

In natural orifice transluminal endoscopic surgery (NOTES) the peritoneal cavity is reached through natural orifices (mouth, rectus and transvaginal duct), by means of little cuttings in the walls of hollow organs. Due to narrow spaces, NOTES needs robotic systems to assure operation/movement precision and patient safety. Variable stiffness actuation (VSA) assures both requirements.

METHODS

The authors developed a grasper for NOTES, provided with VSA, to use as an end-effector for snail robot devices. The present paper deals with basic concepts of VSA and describes the design and architecture of the grasper. Characterization and functional experiments were performed and results analysed.

RESULTS

A finite element model developed for the actuator design was validated, performance grasper characteristic curves were obtained, VSA was validated, and the gripping capability of several objects was assessed.

CONCLUSION

The grasper satisfies technical design specifications. On the basis of the results obtained, a control system can be developed to test grasper in a simulated surgery environment.

Estimating Tool-Tissue Forces Using a 3-Degree-of-Freedom Robotic 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.

Assessment of Tissue Damage due to Mechanical Stresses

While there are many benefits to minimally invasive surgery (MIS), force feedback or touch sensation is limited in the currently available MIS tools, such as surgical robots, creating the potential for excessive force application during surgery and unintended tissue injury. The goal of this work was to develop a methodology with which to identify stress magnitudes and durations that can be safely applied with a MIS grasper to di ferent tissues, potentially improving MIS device design and reducing potentially adverse clinically relevant consequences. Using the porcine model, stresses typically applied in MIS were applied to liver, ureter and small bowel using a motorized endoscopic grasper. Acute indicators of tissue damage including cellular death and infiltration of inflammatory cells were measured using histological and image analysis techniques. Finite element analysis was used to identify approximate stress distributions experienced by the tissues. Parameters used in these finite element models specifically reflected the properties of liver, which served as an initial proxy for all tissues, as stress distributions rather than absolute values were desired. Local regions predicted to have uniform stress by the computational models were mapped to and analyzed in the tissue samples for acute damage. Analysis of variance (ANOVA) and post-hoc analyses were used to detect stress magnitudes and durations that caused significantly increased tissue damage with the goal to ultimately identify safe stress `thresholds' during grasping of the studied tissues. Preliminary data suggests a graded non-linear response between applied stress magnitude and apoptosis in liver and small bowel as well as neutrophil infiltration in the small bowel. The ureter appeared to be more resistant to injury at the tested stress levels. By identifying stress magnitudes and durations within the range of grasping loads applied in MIS, it may be possible for researchers to create a `smart' surgical robot that can guide a surgeon to manipulate tissues with minimal resulting damage. In addition, surgical simulator design can be improved to reflect more realistic tissue responses and evaluate trainees' tissue handling skills.

Sensorless Force Sensing for Minimally Invasive Surgery

Robotic minimally invasive surgery (R-MIS) 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.

Dynamic Modeling of Cable Driven Elongated Surgical Instruments for Sensorless Grip Force Estimation

Haptic feedback plays a key role in surgeries, but it is still a missing component in robotic Minimally Invasive Surgeries. This paper proposes a dynamic model-based sensorless grip force estimation method to address the haptic perception problem for commonly used elongated cable-driven surgical instruments. Cable and cable-pulley properties are studied for dynamic modeling; grip forces, along with driven motor and gripper jaw positions and velocities are jointly estimated with Unscented Kalman Filter and only motor encoder readings and motor output torques are assumed to be known. A bounding filter is used to compensate for model inaccuracy and to improve method robustness. The proposed method was validated on a 10mm gripper which is driven by a Raven-II surgical robot. The gripper was equipped with 1-dimensional force sensors which served as ground truth data. The experimental results showed that the proposed method provides sufficiently good grip force estimation, while only motor encoder and the motor torques are used as observations.

A Novel Device for Measuring Forces in Endoluminal Procedures

In this paper a simple but effective measuring system for endoluminal procedures is presented. The device allows measuring forces during the endoluminal manipulation of tissues with a standard surgical instrument for laparoscopic procedures. The force measurement is performed by recording both the forces applied directly by the surgeon at the instrument handle and the reaction forces on the access port. The measuring system was used to measure the forces necessary for appropriate surgical manipulation of tissues during transanal endoscopic microsurgery (TEM). Ex-vivo and in-vivo measurements were performed, reported and discussed. The obtained data can be used for developing and appropriately dimensioning novel dedicated instrumentation for TEM procedures.