Design Optimization of a Hybrid-Driven Soft Surgical Robot with Biomimetic Constraints.

The current study investigated the geometry optimization of a hybrid-driven (based on the combination of air pressure and tendon tension) soft robot for use in robot-assisted intra-bronchial intervention. Soft robots, made from compliant materials, have gained popularity for use in surgical interventions due to their dexterity and safety. The current study aimed to design a catheter-like soft robot with an improved performance by minimizing radial expansion during inflation and increasing the force exerted on targeted tissues through geometry optimization. To do so, a finite element analysis (FEA) was employed to optimize the soft robot's geometry, considering a multi-objective goal function that incorporated factors such as chamber pressures, tendon tensions, and the cross-sectional area. To accomplish this, a cylindrical soft robot with three air chambers, three tendons, and a central working channel was considered. Then, the dimensions of the soft robot, including the length of the air chambers, the diameter of the air chambers, and the offsets of the air chambers and tendon routes, were optimized to minimize the goal function in an in-plane bending scenario. To accurately simulate the behavior of the soft robot, Ecoflex 00-50 samples were tested based on ISO 7743, and a hyperplastic model was fitted on the compression test data. The FEA simulations were performed using the response surface optimization (RSO) module in ANSYS software, which iteratively explored the design space based on defined objectives and constraints. Using RSO, 45 points of experiments were generated based on the geometrical and loading constraints. During the simulations, tendon force was applied to the tip of the soft robot, while simultaneously, air pressure was applied inside the chamber. Following the optimization of the geometry, a prototype of the soft robot with the optimized values was fabricated and tested in a phantom model, mimicking simulated surgical conditions. The decreased actuation effort and radial expansion of the soft robot resulting from the optimization process have the potential to increase the performance of the manipulator. This advancement led to improved control over the soft robot while additionally minimizing unnecessary cross-sectional expansion. The study demonstrates the effectiveness of the optimization methodology for refining the soft robot's design and highlights its potential for enhancing surgical interventions.

Hyperelastic Modeling and Validation of Hybrid-Actuated Soft Robot with Pressure-Stiffening.

Soft robots have gained popularity, especially in intraluminal applications, because their soft bodies make them safer for surgical interventions than flexures with rigid backbones. This study investigates a pressure-regulating stiffness tendon-driven soft robot and provides a continuum mechanics model for it towards using that in adaptive stiffness applications. To this end, first, a central single-chamber pneumatic and tri-tendon-driven soft robot was designed and fabricated. Afterward, the classic Cosserat's rod model was adopted and augmented with the hyperelastic material model. The model was then formulated as a boundary-value problem and was solved using the shooting method. To identify the pressure-stiffening effect, a parameter-identification problem was formulated to identify the relationship between the flexural rigidity of the soft robot and internal pressure. The flexural rigidity of the robot at various pressures was optimized to match theoretical deformation and experiments. The theoretical findings of arbitrary pressures were then compared with the experiment for validation. The internal chamber pressure was in the range of 0 to 40 kPa and the tendon tensions were in the range of 0 to 3 N. The theoretical and experimental findings were in fair agreement for tip displacement with a maximum error of 6.40% of the flexure's length.

Stiffness Adaptation of a Hybrid Soft Surgical Robot for Improved Safety in Interventional Surgery.

Minimally invasive instruments are inserted per-cutaneously and are steered toward the desired anatomy. The low stiffness of instruments is an advantage; however, once the target is reached, the instrument usually is required to transmit force to the environment. The main limitation of the constant stiffness is predetermined maneuverability and cap of force transmission. Whereas, a highly flexible device can be safely steered through the body but is not suitable for payload limit, while a highly stiff device can have relatively high loads but cannot be steered in highly tortuous trajectories. To overcome this limitation, an adaptive stiffness soft robot was proposed, and the effects of the chamber pressure on the stiffness of the soft robot were investigated. To this end, a single-chamber pneumatic soft robot with one tendon was designed and fabricated. Afterward, a continuum mechanics model based on the nonlinear Cosserat rod model with hyperelastic material model and large deformation kinematics of the robot was developed. The shooting method solved the model as a boundary value problem with Dirichlet and Neumann boundary conditions. The results of the model showed stiffness adaptation feasibility with simultaneous tendon-driving and pneumatic actuation. Thus, to validate the theoretical findings, a series of experimental studies were performed with pressure in the range of 33 to 44 kPa and tendon tensions in the range of 0 to 2.7 N. The theoretical and experimental results for tip displacement and stiffness showed similar trends with a maximum error of 8.25%.

Comparison of Mechanistic and Learning-based Tip Force Estimation on Tendon-driven Soft Robotic Catheters.

Researchers have adopted mechanistic and learning-based approaches for tip force estimation on soft robotic catheters. Typically the literature attributes the mech-anistic methods with more accuracy while indicating the learning-based methods outpace in computational time. In this study, a previously validated mechanistic tip force estimation method was compared with four learning-based methods, i.e. support-vector-regression (SVR), random-forest (RF), Ad-aBoost (Ada), and deep neural network (DNN). The learning-based methods were trained on experimental data acquired from a robotic catheter, developed in-house. The accuracy of force estimation using the five methods were compared with the ground truth forces in a teleoperated catheter manipulation test. Moreover, the capability of the learning-based models in contact detection, i.e., detection of the onset of tip contact, were compared with the ground truth. The results showed that the mechanical model had a mean-absolute error (MAE) of 8.8 mN while the MAE of SVR, RF, Ada, and DNN were 5.6, 5.2, 5.3, and 5.1 mN, respectively. Moreover, the accuracy and precision of the mechanistic model for contact detection was 89.2% and 91.7%, respectively, while these were 97.0%, 97.7%, 97.6%,and 97% and 97.9%, 98.3%, 97.8%, and 98.8% for the SVR, RF, Ada, and DNN, respectively. The comparison showed that with hyper-parameter optimization the learning-based models surpassed the mechanistic model in accuracy and precision, while both method approaches revealed acceptable performance for the proposed application.

Design of a Linear Wavenumber Spectrometer for Line Scanning Optical Coherence Tomography with 50 mm Focal Length Cylindrical Optics.

Optical coherence tomography (OCT) has a wide range of uses in bioimaging and nondestructive testing. Larger bandwidth light sources have recently been implemented to enhance measurement resolution. Increased bandwidth has a negative impact on spectral nonlinearity in k space, notably in the case of spectral domain OCT (SD-OCT). This nonlinearity reduces the depth-dependent signal sensitivity of the spectrometers. A grating and prism combination is extensively used for linearizing. In an earlier study, we used a combination of the reflective grating and prism, as well as a cylindrical mirror with a radius of 180 mm, to achieve a high SR ratio with low nonlinearity. A creative design for a spectrometer with a cylindrical mirror of radius 50 mm, a light source with a center wavelength of 830 ± 100 nm (µm-1 - 6.756 µm-1 in k-space), and a grating of 1600 lines/mm is presented in this work. The design optimization is performed using MATLAB and ZEMAX. In the proposed design, the nonlinearity error reduced from 157∘× µm to 10.75∘× µm within the wavenumber range considered. The sensitivity research revealed that, with the new design, the SR ratio is extremely sensitive to the imaging optics' angles. To resolve this, a spectrometer based on Grism is introduced. We present a Grism-based spectrometer with an optimized SR ratio of 0.97 and nonlinearity of 0.792∘× µm (Δθ/Δk). According to the sensitivity study, the Grism-based spectrometer is more robust.

Design and Optimization of a Linear Wavenumber Spectrometer with Cylindrical Optics for Line Scanning Optical Coherence Tomography.

We report the design of a high-efficiency spectral-domain spectrometer with cylindrical optics for line scanning optical coherence tomography (OCT). The spectral nonlinearity in k space (wavenumber) lowers the depth-dependent signal sensitivity of the spectrometers. For linearizing, in this design, grating and prism have been introduced. For line scanning, a cylindrical mirror is utilized in the scanning part. Line scanning improves the speed of imaging compared to fly-spot scanning. Line scanning OCT requires a spectrometer that utilizes cylindrical optics. In this work, an optical design of a linear wavenumber spectrometer with cylindrical optics is introduced. While there are many works using grating and prism to linearize the K space spectrometer design, there is no work on linearizing the k-space spectrometer with cylindrical optics for line scanning that provides high sensitivity and high-speed imaging without the need for resampling. The design of the spectrometer was achieved through MATLAB and ZEMAX simulations. The spectrometer design is optimized for the broadband light source with a center wavelength of 830 ± 100 nm (8.607 µm-1- 6.756 µm-1 in k-space). The variation in the output angle with respect to the wavenumber can be mentioned as a nonlinearity error. From our design results, it is observed that the nonlinearity error reduced from 147.0115 to 0.0149 Δθ*µm within the wavenumber range considered. The use of the proposed reflective optics for focusing reduces the chromatic aberration and increases image quality (measured by the Strehl ratio (SR)). The complete system will provide clinicians a powerful tool for real-time diagnosis, treatment, and guidance in surgery with high image quality for in-vivo applications.

Optical Fiber Array Sensor for Force Estimation and Localization in TAVI Procedure: Design, Modeling, Analysis and Validation.

Transcatheter aortic valve implantation has shown superior clinical outcomes compared to open aortic valve replacement surgery. The loss of the natural sense of touch, inherited from its minimally invasive nature, could lead to misplacement of the valve in the aortic annulus. In this study, a cylindrical optical fiber sensor is proposed to be integrated with valve delivery catheters. The proposed sensor works based on intensity modulation principle and is capable of measuring and localizing lateral force. The proposed sensor was constituted of an array of optical fibers embedded on a rigid substrate and covered by a flexible shell. The optical fibers were modeled as Euler-Bernoulli beams with both-end fixed boundary conditions. To study the sensing principle, a parametric finite element model of the sensor with lateral point loads was developed and the deflection of the optical fibers, as the determinant of light intensity modulation was analyzed. Moreover, the sensor was fabricated, and a set of experiments were performed to study the performance of the sensor in lateral force measurement and localization. The results showed that the transmitted light intensity decreased up to 24% for an external force of 1 N. Additionally, the results showed the same trend between the simulation predictions and experimental results. The proposed sensor was sensitive to the magnitude and position of the external force which shows its capability for lateral force measurement and localization.

Corrigendum: Deep Learning-Based Haptic Guidance for Surgical Skills Transfer.

[This corrects the article DOI: 10.3389/frobt.2020.586707.].

Toward Task Autonomy in Robotic Cardiac Ablation: Learning-Based Kinematic Control of Soft Tendon-Driven Catheters.

The goal of this study was to propose and validate a control framework with level-2 autonomy (task autonomy) for the control of flexible ablation catheters. To this end, a kinematic model for the flexible portion of typical ablation catheters was developed and a 40-mm-long spring-loaded flexible catheter was fabricated. The feasible space of the catheter was obtained experimentally. Furthermore, a robotic catheter intervention system was prototyped for controlling the length of the catheter tendons. The proposed control framework used a support vector machine classifier to determine the tendons to be driven, and a fully connected neural network regressor to determine the length of the tendons. The classifier and regressors were trained with the data from the feasible space. The control system was implemented in parallel at user-interface and firmware and exhibited a 0.4-s lag in following the input. The validation studies were four trajectory tracking and four target reaching experiments. The system was capable of tracking trajectories with an error of 0.49 ± 0.32 and 0.62 ± 0.36 mm in slow and fast trajectories, respectively. Also, it exhibited submillimeter accuracy in reaching three preplanned targets and ruling out one nonfeasible target autonomously. The results showed improved accuracy and repeatability of the position control compared with the recent literature. The proposed learning-based approach could be used in enabling task autonomy for catheter-based ablation therapies.

Sensor-free Force Control of Tendon-driven Ablation Catheters through Position Control and Contact Modeling.

In the present study, a sensor-free force control framework for tendon-driven steerable catheters was proposed and validated. The hypothesis of this study was that the contact force between the catheter tip and the tissue could be controlled using the estimated force with a previously validated displacement-based viscoelastic tissue model. The tissue model was used in a feedback control loop. The model estimated the contact force based on a realtime estimation of catheter-tissue indentation depth performed by a data-driven inverse kinematic model. To test the hypothesis, a tendon-driven catheter (φ6 × 40mm) and a robotic catheter intervention system were prototyped and characterized. Three validation studies were performed to test the performance of the proposed system with static and dynamic inputs. The results showed that the system was capable of reaching to the desired force with a root-mean-square error of 0.03 ± 0.02N for static tests and 0.05 ± 0.04N for dynamic inputs. The main contribution of this study was providing a computationally efficient and sensor-free force control schema for tendon-driven catheters.

Development and assessment of a stiffness display system for minimally invasive surgery based on smart magneto-rheological elastomers.

In the present study, a solution to address the clinical need for stiffness display during manual and robotic minimally invasive surgery was postulated, developed, and assessed. To this end, a magneto-rheological elastomer-based stiffness display, MiTouch, was designed, developed, and analyzed. The mechanical properties of the MRE and system parameters were identified experimentally, based on which the force-field-stiffness response surface of the smart MRE was characterized. Based on the response surface, a stiffness controller was designed and verified for a set of performance requirements. A heartbeat simulation experiment showed the capability of the system for replicating desired tactile forces through stiffness control. Also, the system successfully attained an arbitrarily selected stiffness (4 N/mm) and maintained it within a bounded range (4.07 ± 0.41 N/mm). A comparison of the system performance with current literature validated its applicability for the proposed medical application.

Deep Learning-Based Haptic Guidance for Surgical Skills Transfer.

Having a trusted and useful system that helps to diminish the risk of medical errors and facilitate the improvement of quality in the medical education is indispensable. Thousands of surgical errors are occurred annually with high adverse event rate, despite inordinate number of devised patients safety initiatives. Inadvertently or otherwise, surgeons play a critical role in the aforementioned errors. Training surgeons is one of the most crucial and delicate parts of medical education and needs more attention due to its practical intrinsic. In contrast to engineering, dealing with mortal alive creatures provides a minuscule chance of trial and error for trainees. Training in operative rooms, on the other hand, is extremely expensive in terms of not only equipment but also hiring professional trainers. In addition, the COVID-19 pandemic has caused to establish initiatives such as social distancing in order to mitigate the rate of outbreak. This leads surgeons to postpone some non-urgent surgeries or operate with restrictions in terms of safety. Subsequently, educational systems are affected by the limitations due to the pandemic. Skill transfer systems in cooperation with a virtual training environment is thought as a solution to address aforesaid issues. This enables not only novice surgeons to enrich their proficiency but also helps expert surgeons to be supervised during the operation. This paper focuses on devising a solution based on deep leaning algorithms to model the behavior of experts during the operation. In other words, the proposed solution is a skill transfer method that learns professional demonstrations using different effective factors from the body of experts. The trained model then provides a real-time haptic guidance signal for either instructing trainees or supervising expert surgeons. A simulation is utilized to emulate an operating room for femur drilling surgery, which is a common invasive treatment for osteoporosis. This helps us with both collecting the essential data and assessing the obtained models. Experimental results show that the proposed method is capable of emitting guidance force haptic signal with an acceptable error rate.

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.

Flow force augmented 3D suspended polymeric microfluidic (SPMF3 ) platform.

Detection and study of bioelements using microfluidic systems has been of great interest in the biodiagnostics field. Microcantilevers are the most used systems in biodetection due to their implementation simplicity which have been used for a wide variety of applications ranging from cellular to molecular diagnosis. However, increasing further the sensitivity of the microcantilever systems have a great effect on the cantilever based sensing for chemical and bio applications. In order to improve further the performance of microcantilevers, a flow force augmented 3D suspended microchannel is proposed using which microparticles can be conveyed through a microchannel inside the microcantilever to the detection area. This innovative microchannel design addresses the low sensitivity issue by increasing its sensitivity up to 5 times than the earlier reported similar microsystems. Moreover, fabricating this microsystem out of Polydimethylsiloxane (PDMS) would eliminate external exciter dependency in many detection applications such as biodiagnostics. In this study, the designed microsystem has been analyzed theoretically, simulated and tested. Moreover, the microsystem has been fabricated and tested under different conditions, the results of which have been compared with simulation results. Finally, its innovative fabrication process and issues are reported and discussed.

Upcoming Methods and Specifications of Continuous Intraocular Pressure Monitoring Systems for Glaucoma.

Glaucoma is the leading cause of irreversible blindness and vision loss in the world. Although intraocular pressure (IOP) is no longer considered the only risk factor for glaucoma, it is still the most important one. In most cases, high IOP is secondary to trabecular meshwork dysfunction. High IOP leads to compaction of the lamina cribrosa and subsequent damage to retinal ganglion cell axons. Damage to the optic nerve head is evident on funduscopy as posterior bowing of the lamina cribrosa and increased cupping. Currently, the only documented method to slow or halt the progression of this disease is to decrease the IOP; hence, accurate IOP measurement is crucial not only for diagnosis, but also for the management. Due to the dynamic nature and fluctuation of the IOP, a single clinical measurement is not a reliable indicator of diurnal IOP; it requires 24-hour monitoring methods. Technological advances in microelectromechanical systems and microfluidics provide a promising solution for the effective measurement of IOP. This paper provides a broad overview of the upcoming technologies to be used for continuous IOP monitoring.

Hybrid piezoresistive-optical tactile sensor for simultaneous measurement of tissue stiffness and detection of tissue discontinuity in robot-assisted minimally invasive surgery.

To compensate for the lack of touch during minimally invasive and robotic surgeries, tactile sensors are integrated with surgical instruments. Surgical tools with tactile sensors have been used mainly for distinguishing among different tissues and detecting malignant tissues or tumors. Studies have revealed that malignant tissue is most likely stiffer than normal. This would lead to the formation of a sharp discontinuity in tissue mechanical properties. A hybrid piezoresistive-optical-fiber sensor is proposed. This sensor is investigated for its capabilities in tissue distinction and detection of a sharp discontinuity. The dynamic interaction of the sensor and tissue is studied using finite element method. The tissue is modeled as a two-term Mooney­Rivlin hyperelastic material. For experimental verification, the sensor was microfabricated and tested under the same conditions as of the simulations. The simulation and experimental results are in a fair agreement. The sensor exhibits an acceptable linearity, repeatability, and sensitivity in characterizing the stiffness of different tissue phantoms. Also, it is capable of locating the position of a sharp discontinuity in the tissue. Due to the simplicity of its sensing principle, the proposed hybrid sensor could also be used for industrial applications.

Micro-optical force distribution sensing suitable for lump/artery detection.

Surgeons performing robotic-assisted surgical tasks need to establish the density and constituency of hidden tissue structures using only surgical tools. This is possible by integrating a miniaturized sensor into the end-effectors of robotic surgical systems. In this present work, optical microsystems technology is utilized to develop a miniature force-distribution sensor that can be integrated into surgical end-effectors. The sensing principle of the sensor is based on the mechanism of splice coupling. Since the device is fully optical, the sensor is magnetic-resonance compatible and is also electrically passive. The experimental results performed on the developed sensor confirm its ability to measure the distributed force information. Such information is used to detect different tissue structures such as lumps, arteries, or ureters during robotic-assisted surgical tasks.

A proof-of-principle robot with potential for the development of a hand-held tactile instrument for minimally-invasive artery cross-clamping.

One of the most common diseases of the vascular system is abdominal aortic aneurysm (AAA), for which the most definitive treatment is surgery. Minimally invasive aorta surgery is a novel method of surgery performed through small incisions and offers significant advantages including less pain, shorter hospital stay, faster patient recovery, less possibility of infection, etc. However, lack of sense of touch is the main drawback of this type of aorta surgery that would incapacitate the surgeon to exactly distinguish the aorta from its surrounding tissues which could cause various problems during the aorta cross-clamping process. One of the most important drawbacks is that it makes the aorta cross-clamping process the most time-consuming process of aortic repair surgery. The artificial tactile sensing approach is a novel method that can be used in various fields of medicine and, more specifically, in minimally invasive surgeries, where using the 'tactile sense' is not possible. In this paper, considering the present problems during aortic-repair-laparoscopy and imitating the movement of surgeons' fingers during aorta cross-clamping, a novel tactile-based artery cross-clamping robot is introduced and its function is evaluated experimentally. It is illustrated that this new tactile-based artery cross-clamping robot is well capable of dissecting an artery from its adjacent tissues in a short time with an acceptable accuracy.

Innovative optical microsystem for static and dynamic tissue diagnosis in minimally invasive surgical operations.

During conventional surgical tasks, surgeons use their tactile perception in their finger tips to sense the degree of softness of biological tissues to identify tissue types and to feel for any abnormalities. However, in robotic-assisted surgical systems, surgeons are unable to sense this information because only surgical tools interact with tissues. In order to provide surgeons with such useful tactile perception, therefore, a tactile sensor is required that is capable of simultaneously measuring contact force and resulting tissue deformation. Accordingly, this paper discusses the design, prototyping, testing, and validation of an innovative tactile sensor that is capable of measuring the degree of softness of soft objects such as tissues under both static and dynamic loading conditions and which is also magnetic resonance compatible and electrically passive. These unique characteristics of the proposed sensor would also make it a practical choice for use in robotic-assisted surgical platforms. The prototype version of this sensor was developed by using optical micro-systems technology and, thus far, experimental test results performed on the prototyped sensor have validated its ability to measure the relative softness of artificial tissues.

Viscoelastic modeling of the contact interaction between a tactile sensor and an atrial tissue.

Modeling and parameter identification of soft tissue are essential in establishing an accurate contact model for tool-tissue interaction, which can be used in the development of high-fidelity surgical instruments. This paper discusses the interaction between a tissue and a tactile sensor in minimally invasive surgery, the focus being a novel technique for robotic-assisted mitral valve repair, in which tactile sensors are used to distinguish between different kinds of tissue by their relative softness. A discrete viscoelastic model is selected to represent the tissue behavior. To populate the model of the tissue with actual data, a set of tissue-testing experiments is designed and implemented on the atrial tissue of a swine heart by analyzing its dynamic response. By means of a genetic algorithm, data of the complex compliance are extracted and used to find the coefficients of the model. Further, a viscoelastic contact model is developed to model the interaction between the tissue and the tactile sensor with annular shape. Finally, the relation among the indentation displacement, the ratio of the radii, and the applied force is established parametrically.