ABSTRACT. Probe-based Confocal Laser Endomicroscopy (pCLE) is a cutting-edge imaging technique that allows for real-time, in-vivo, and in-situ visualization of cellular tissue structures during surgical procedures. This technology offers a significant advantage by providing detailed information about cellular tissue morphology, which can help surgeons make more informed decisions intraoperatively. To acquire high-quality pCLE images while scanning tissue, it is crucial to maintain optimal contact between the probe and the tissue, and to keep the probe perpendicular to the tissue surface. To tackle this challenge, we have designed advanced microscopic vision-based deep learning models to provide visual feedback for robotic tissue scanning. More specifically, the Spatial-Frequency Feature Coupling Network (SFFC-Net) and the Probe Orientation Vision Transformer (PO-ViT) have been developed for estimating pCLE probe-tissue distance and probe orientation, respectively. By utilizing these deep learning models, the robotic scanning system can dynamically adjust the pose of the pCLE probe in response to real-time visual feedback. The ultimate goal is to guide the robotic scanning system in positioning the pCLE probe optimally relative to the tissue surface, enhancing scanning accuracy and image quality. This, in turn, facilitates accurate diagnosis and surgical decision-making, leading to improved patient outcomes and overall surgical efficiency.

ABSTRACT. The abstract for "MedSAM-Flow: A Deep Fusion Methodology for Robust Realtime Tracking of Objects in Laparoscopic Videos" by Marzie Lafouti, Liane S. Feldman, and Amir Hooshiar from the Surgical Performance Enhancement and Robotics Centre (SuPER), Department of Surgery, McGill University, Montreal, Canada, introduces a pioneering approach for real-time surgical instrument segmentation in laparoscopic videos. The study leverages the MedSAM model, optimized for medical image segmentation, in conjunction with Optical Flow and Bezier methods to overcome the limitations of slow execution times, ensuring fast and efficient real-time video segmentation. This novel methodology not only enables precise real-time segmentation and smooth tracking of surgical instruments across video frames but also facilitates instantaneous visual feedback for surgeons, enhancing surgical precision and patient care.

The research integrates advanced AI techniques with established computer vision algorithms, achieving remarkable accuracy in real-time segmentation during gastrointestinal surgeries. By periodically loading MedSAM and employing Optical Flow for dynamic tracking, along with Bezier methods for smooth curve interpolation, the approach ensures seamless instrument tracking and segmentation across video frames. This integration proves significantly more efficient than existing models, offering a practical solution for real-time applications in surgical settings.

Results from this study indicate that the MedSAM-Flow methodology meets the real-time performance criteria for laparoscopic surgery, with substantial improvements in computational efficiency and accuracy over traditional methods. The proposed approach not only enhances surgical technique and patient outcomes by providing immediate feedback and facilitating skill assessment but also sets the foundation for future AI-driven surgical innovations.

This work not only addresses a critical need in surgical practice but also opens avenues for further research and development of AI technologies in medicine. By demonstrating the feasibility and effectiveness of real-time surgical instrument segmentation, ultimately aiming to improve surgical practices and patient care standards through advanced AI applications.

ABSTRACT. Surgical procedures are characterised by specific movements of the surgeon’s hands to complete tasks such as suturing, cutting, or object relocation. Understanding the context and kinematics of these procedures can allow us to predict the goal that the surgeon is trying to achieve and provide the correct external guidance. In this paper, we develop a real-time surgical gesture recognition method for shared control in robotic surgical tasks. We implement Long Short-Term Memory (LSTM) and Transformers-based methods to verify their performance for real-time applications. To prove the effectiveness of our methods, we evaluate and assess it on an existing dataset. We demonstrate that a high performance can be achieved for real-time recognition of kinematic surgical gestures by categorising the suturing task in four essential surgeme motions and one for general movements.

ABSTRACT. In 2021, Cardiovascular Diseases (CVDs) were attributed to 20.5 million deaths worldwide, representing a third of all global mortality annually and positioning CVDs as the predominant cause of death. Right Heart Catheterization (RHC) has emerged as an exceptionally effective clinical procedure for diagnosing some conditions of CVDs. Concurrently, there is a burgeoning interest in harnessing machine learning (ML) and artificial intelligence (AI) technologies to interventional robots with autonomous capabilities. This study unveils a novel learning-based robotic system designed for the 3D navigation of catheters, employing Sim-to-Real transfer techniques with a particular emphasis on Right Heart Catheterization (RHC).

ABSTRACT. Skilled sonographers have the incredible ability to look at 2D ultrasound images and recreate in their minds a 3D understanding of the anatomy they are investigating. Given the noisy images and the limited context of tomographic slices, creating a 3D model from 2D, images is undeniably challenging. In the context of robotic ultrasound systems, building 3D volumes of the tissue conventionally relies on compounding, where images taken at various robot poses fill the voxels in a 3D volume. However compounding uses interpolation to fill the inherent gaps in the 3D volumes, and current interpolation methods tend to not generalize well. Interpolation methods often require hand-tuned parameters or are tailored to the specific anatomy. Further, interpolation over large gaps can produce implausible content in the compounded volumes. Finally, storing and manipulating these volumes also demands considerable memory.

These fundamental challenges with typical volume reconstruction methods motivated the development of Ultra-NeRF, a neural implicit representation for medical ultrasound. It estimates tissue properties from multi-view image data and learns an implicit 3D ultrasound volume. The method yields smooth interpolation and physically plausible novel views. Ultra-NeRF has previously only been tested on relatively simple ultrasound images, either generated from simulations or robotically captured from medical phantoms. In order to test the applicability of Ultra-NeRF to real world in-vivo data, we applied the method to ultrasound images captured robotically from live pigs. It was observed that Ultra-NeRF did not capture high-frequency features well, struggled with seamless interpolation between observations and produced artifacts caused due to unstableregression.

In this work, we present a improved Ultra-NeRF framework that improves rendering performance on more complex live tissues. We achieve this by modifyingthe network architecture and introducing a new training schedule.

ABSTRACT. Introduction: In Transperineal Focal Laser Ablation (TPLA), needles are used to position an optical fibre near a tumour to treat prostate cancer. Commonly used needles are bound to linear trajectories, which might cause access restriction because of anatomical obstacles or targeting errors caused by needle-tissue interaction. This study presents a wasp-inspired needle that can steer and self-propel through a tissue phantom to position an optical fibre with zero external push force. Materials and methods: The wasp-inspired needle design consists of six parallel 0.25-mm diameter Nitinol rods driven by a 3D-printed manual actuation system. The needle achieves a self-propelled motion by advancing one needle segment while retracting others, where the combined friction force of five retracting segments overcomes the sum of the friction and cutting forces of the advancing segment. Steering is achieved by creating an offset between the needle segments to approximate a bevel-shaped tip using a global steering unit at the needle handle. The self-propelling performance of the needle with integrated fibre in its lumen was evaluated in gelatine phantoms in terms of the slip ratio of the needle with respect to the gelatine phantom. Steering was evaluated based on the ratio of the needle deflection from the straight path to the insertion depth. Results: The evaluation showed that the needle with integrated optical fibre could advance through the gelatine phantoms with a slip ratio of 0.79-0.88. The maximum achieved deflection-to-insertion ratio was 0.088 for steering towards the right. Discussion: The low deflection-to-insertion ratio can partially be explained by needle rotation along its length due to its low torsion stiffness and the cam path that induces a slight bevel offset in the needle’s straight configuration. The proposed bioinspired needle design integrated with an optical fibre is a step towards developing steerable needles for TPLA to treat prostate cancer.

ABSTRACT. This study presents a novel magnetic navigation system designed to enhance the precision and efficiency of cardiac ablation procedures. The system comprises two key components: a specially designed catheter embedding a series of spherical permanent magnets, and an innovative actuation system equipped with two rotating permanent magnets. This unique configuration allows for a more compact and clinically adaptable design compared to traditional systems.

Experimental results show that this system offers improvements in operation speed and ease, compared to manual catheters.

ABSTRACT. This paper introduces a novel multi-Degree of Freedom tendon-driven steerable sheath designed for precise positioning in percutaneous Left Atrial Appendage Closure (LAAC). The proposed steerable sheath integrates a motorized system controlling a Nitinol tip with tailored stiffness and independent bending capabilities, enhancing co-axial alignment with the LAA for precise device implantation. The design, fabrication, and experimental characterization of the sheath are detailed, demonstrating promising bending capabilities and interaction forces. This innovative approach holds potential for improving LAAC procedures by addressing current limitations in device delivery and positioning.

ABSTRACT. Utilizing an endoscopic approach to resect intraventricular brain tumours is associated with reduced morbidity and shorter recovery times. During endoscopic resection, surgeons commonly use a motorized shaver which fragments the tumour and suctions it from the body. However, a drawback of existing shavers is that they possess straight, rigid, shafts. As a result, lateral movement of the tip is accomplished by angling/pivoting the tool, which can deform and damage brain parenchyma. To increase a surgeon’s range of motion without relying on pivoting, concentric tube robots (CTRs) are being developed for neurosurgery. However, existing straight/rigid shavers are not suitable for use through CTRs as they deform the robots’ shape. As such, the objective of this research was to develop a flexible and thus CTR-compatible tissue shaver.

The flexible shaver was created by modifying the Nico Myriad, an existing neurosurgical shaver. The device’s shaft was rebuilt with flexible components, namely a notched nitinol cannula and polyimide sheath. Testing was performed to determine the rate at which the shaver could resect agar gel when bent to a 5 cm radius of curvature (simulating use through a CTR). Shaft bending stiffness was measured and applied in MATLAB simulations to quantify the effect of shaver insertion on CTR tip position. Finally, the workspace volume of a CTR-mounted shaver was calculated.

Results showed that the flexible shaver resects agar at a rate equivalent to the rigid tool, even when curved. The bending stiffness of the shaft was 537 newton square millimeters, which only induced a maximum 1.1 mm change in CTR tip position. Furthermore, the predicted workspace volume of a CTR-mounted shaver was 9,647 cubic millimeters, exceeding that of a straight tool pivoted 5 degrees. From these results, we conclude that our flexible shaver is CTR-compatible, while still maintaining the tissue resection capabilities of rigid devices.

ABSTRACT. Endovascular catheterization plays a crucial role in treating various cardiovascular conditions such as aortic valve stenosis and coronary heart disease, with over 200 million catheters utilized annually. The insertion of catheters into blood vessels inevitably creates friction between the catheter and vessel wall. This generated friction is one of the most significant sources of prevalent cardiovascular intervention complications such as arterial spasm, hematoma and vascular trauma. Despite its complications, frictional interaction remains critical for ensuring catheter stability, especially during cutting or puncturing operations which require significant forces. Thus, managing this frictional interaction is essential for ensuring optimal patient outcomes. In response to this need, we previously introduced the concept of a friction programmable catheter, equipped with discrete friction control modules along its shaft to toggle between high and low friction states on demand. In this paper, we present an enhanced iteration of these friction control modules, addressing the limitations of the earlier design resulting in improved performance and miniaturization. Our sliding friction experiments on ex-vivo porcine aorta tissue demonstrate that the enhanced miniaturized friction control modules can reduce friction by up to 42%, with an average reduction of 35% across all tissue samples. These results underscore the viability of the design and its potential to enhance the safety and efficacy of minimally invasive endovascular procedures.

ABSTRACT. This paper presents a new concept that has the potential to miniaturize the driving mechanism of Programmable Bevel-Tip Needles. The study utilized a custom-designed test rig and advanced video analysis techniques to assess potential slippage between segments and gears. The results suggest that gears made from softer materials had poorer engagement with the needle, while gears that were too hard had a smooth and slippery surface that resulted in large amounts of slip. After iterative testing, an optimal material composition of 60% hard and 40% soft was identified, along with an optimal normal force. However, slipping issues must be addressed to realize the potential of this new concept fully, and future experimental studies are planned to consider different teeth profiles and the size of teeth on the needle and wheels. Overall, this study provides useful insights into the potential of this new concept and highlights areas for future research, including a methodology for testing the new mechanism and measuring slippage.

ABSTRACT. Advances in medical imaging modalities (e.g. ultrasound, computed tomography, and MRI) have led to improvements in image-guided needle interventions, such as biopsy and radiation ablation. Traditionally, radiologists would perform interventional procedures freehand under the guidance of an imaging system (i.e. to track the position of the needle during alignment and insertion). Such procedures require high motor-visual coordination from the radiologist and are time-consuming, with positional accuracy highly dependent on experience. This abstract presents the operating principles of the compliant mechanism-based needle targeting system with preliminary open-air test results given.

ABSTRACT. Bevel tip steerable needles have been adapted to a wide variety of medical interventions, where their ability to steer through curved insertion paths is helpful for increasing accuracy and avoiding anatomical obstacles. The traditional paradigm is to use the bevel tip steerable needle in a manner analogous to a catheter's guidewire, where an external sheath is passed over it after insertion, for therapy delivery. However, it may sometimes be desirable to leave the needle in place while delivering therapy, either to maintain magnetic tracking, or to eliminate the possibility of sheath motion relative to anatomy during needle withdrawal. Here, we present a bevel tip steerable needle with an integrated fluid channel, which enables liquid injection through the needle itself. We demonstrate use of this needle and injection of contrast agent into in vivo porcine lungs.

ABSTRACT. Needle-based interventions are critical in procedures such as blood drawing, endovascular device insertion, and biopsy. However, freehand needle insertion to deep targets risks damaging critical anatomic structures. Robotic assistance can help guide the needle to reach its target while avoiding these structures, especially in scenarios where skilled specialists may not be readily available, e.g. rural areas and battlefields. Robotic assistance requires real-time imaging and computer vision to monitor the needle’s shape and position during insertion. Compared to options like MRI and CT, point-of-care ultrasound imaging is especially appropriate for this task due to its benefits of real-time video, portability, low cost, and lack of ionizing radiation. Despite these benefits, ultrasound suffers from poor image quality, making it difficult for both humans and computer vision algorithms to track the needle. Needle bending, partially due to interference from heterogeneous tissue layers, is another challenge. These challenges motivate the need for an effective deformable registration method for needle tracking in ultrasound. Classical methods address deformable registration through an optimization approach. Despite early successes with these methods, they can have poor accuracy, be computationally costly, and involve tuning parameters. Recently, deep learning methods have been embraced to address these limitations. One approach, upon which we build our present work, is to represent deformations as optical flow and train a neural network to predict the optical flow vector field. Traditionally this requires ground-truth flow maps for regression, but the scarcity of ground-truth data in medical imaging poses a significant hurdle to training these models. To address these issues, we present an unsupervised learning-based approach to deformable registration for needle tracking in ultrasound. In our prior work, we introduced U-RAFT, a model for deformable registration in vessels. Here, we build upon to calculate flow maps for video sequences of needles, an approach we call Video U-RAFT.

ABSTRACT. Optic nerve sheath fenestration (ONSF) is used to treat increased intracranial pressure caused by craniocerebral injury. The operation usually requires the detachment of the eye muscles and cutting open part of the skull to access the nerve behind the eye in the eye orbit [1]. Severe potential complications such as visual loss by making a deep incision that damages the nerve fibres is another challenge with ONSF. To achieve minimally invasive ONSF, we have recently proposed a multi-arm Concentric Tube Robot (CTR), consisting of a camera and a suction cup-equipped needle (called Gripe-Needle) arm (see Fig. 1a) [2], [3]. The compliant miniature size of the robot enables performing ONSF by bypassing the eye globe in the eye orbit through a small collimator (incision port) that is sutured to the eye globe. The Gripe-Needle uniformly and gently grasps the incision area vicinity by suction force. This eliminates the distance between the gripping and incision sites and the challenges with estimating the incision depth due to the resulted complex deformation of the tissue [3]. Ex-vivo evaluation of the earlier design of Gripe-Needle showed successful grasping and manipulation of different porcine eye tissues. However, a successful incision while maintain the optic nerve tissue could not be achieved [3]. In this paper, we revisited the geometry and material properties of the Gripe-Needle to address this issue.

ABSTRACT. Real-time video is vital in surgery for immediate visual information, precise actions, education, and post-operative analysis. Traditional streaming protocols like RTP face challenges in meeting real-time requirements and transporting metadata alongside surgical video. The Data Distribution Service (DDS) emerges as a promising solution for surgical systems, known for its use for communication in medical robotic systems and as the default middleware within ROS2.

GStreamer was used to create video processing pipelines for evaluation between RTP and DDS. DDS, implemented with RTI Connext, demonstrated lower processing latency compared to RTP, by eliminating the need for RTP payloading/depayloading. Quality-of-Service (QoS) tuning in DDS optimized the transport for large surgical video data. DDS also maintained reliability at higher resolutions while RTP over UDP experienced dropped frames.

The flexibility of DDS offers a common framework for data flow and live video correlation in surgical applications without compromising performance. DDS's unified framework benefits various medical use cases, offering real-time clinical guidance, workflow improvements, procedure assessments, device usage, and autonomous instrument control. In summary, DDS proves to be a superior protocol for video streaming in surgical applications, addressing challenges posed by legacy protocols like RTP.

ABSTRACT. In high-risk cardiac operating rooms (ORs), the cognitive alignment of surgical teams is critical for performance and patient safety. This study investigates the cognitive processes in cardiac surgery teams, focusing on potential misalignments among surgeons, anesthesiologists, and perfusionists during coronary artery bypass grafting (CABG) procedures. Through Cognitive Task Analysis of 9 expert participants, we examined decision-making, communication, and problem-solving strategies across CABG phases. We quantified cognitive process misalignments, revealing 137 unique intraoperative cognitive processes with significant variations in perceived cognitive workload across different surgical steps. Misalignment analysis identified specific phases with notable discrepancies, such as “clamp aorta and deliver cardioplegia” and “anastomoses,” where the misalignment scores were 12 and 10, respectively, between surgeons and anesthesiologists. A Spearman correlation analysis also yielded a coefficient of 0.42 (p < 0.01), indicating a positive correlation between team-level perceived cognitive load and misalignment. These results highlight the need for targeted interventions to improve team coordination and cognitive alignment in cardiac surgery, potentially enhancing patient care and efficiency. This study also provides a preliminary data-driven framework for understanding team dynamics in high-pressure medical environments and informs the development of training programs to foster cognitive alignment in surgical teams.

ABSTRACT. This study presents the xAI-SURG framework, a clinician-centered explainable artificial intelligence (xAI) approach for decision support in the operating room (OR). It addresses the need for explainability in AI systems for enhanced clinician trust and understanding, crucial in high-stakes environments like the OR. The study involved semi-structured interviews with expert perfusionists, focusing on their decision-making during Goal-Directed Perfusion (GDP) in cardiac surgery. A Cognitive Task Analysis (CTA) map was developed, revealing complex decision-making processes. The xAI-SURG framework integrates the Recognition-Primed Decision-Making (RPDM) model with CTA, aligning with perfusionists' cognitive workflows. It aims to enhance patient safety and outcomes by supporting clinicians' naturalistic decision-making with transparent, interpretable AI insights. This paper discusses broader implications for AI in healthcare, emphasizing the balance between AI-driven recommendations and human expertise. Future research directions include longitudinal studies and interface development for broader surgical applications.

ABSTRACT. A-traumatically gripping slippery and delicate tissues during Minimally Invasive Surgery (MIS) presents a frequent challenge. Conventional tissue grippers often rely on serrated surfaces and high pinch forces for sufficient grip, posing a risk for tissue trauma. In contrast, our proposed solution introduces an expandable suction gripper that exerts pull forces directly in line with the instrument shaft, eliminating the need to enclose the tissue for a secure grip. The suction gripper fits through a ∅10 mm trocar and expands its suction surface when the suction tip is rotated. The rigid design of the suction tip minimises leakage risk from inward slip of the suction surface, whilst multiple independently actuated suction discs mitigate the risk of tissue loss due to leakage. Experiments demonstrated improved attachment performance with rigid suction tips featuring multiple suction discs on phantom tissues with varying stiffness and curvature. Notably, whereas the shape of the phantom tissue has a significant effect on the attachment force using a single suction disc, the effect is minimal for the multiple suction disc configuration. In conclusion, our suction gripper shows potential for a safer alternative to conventional tissue grippers in MIS.

ABSTRACT. Robot-assisted surgery (RAS) poses challenges in skills acquisition due to the absence of haptic feedback, potentially leading to adverse intraoperative events. This study focuses on a high-fidelity vascular simulator equipped with a soft strain sensor to assess its construct validity and its ability to differentiate between surgical specialties in novice operators. The simulator, featuring a plug-and-play design, replicates vascular and surrounding tissue anatomy. A resistive stretching sensor integrated into the vein objectively measures vessel elongation. Mechanical characterizations through tensile and compressive tests validate anatomical fidelity.

An international multicentric study, involving participants from two academic institutions, categorizes users into novices, fellows, and experts based on their RAS experience. Participants perform a standardized surgical task involving the dissection of a vascular structure. The simulator's ability to discriminate between expertise levels and surgical specialties is evaluated. The simulator was able to distinguish between three different levels of surgical experience considering the median elongation of the vessel during the task.

During the second repetition a statistical significant difference between the three groups was found (p-value of 0.02). In addition, a difference across novice in General surgery and Urology during the second task repetition was assessed with p-value of 0.05.

The study suggests the simulator's potential as a training tool for RAS, with plans for further data collection, comprehensive analysis, and integration into training curricula. Future clinical evaluations comparing surgeons who used the simulator against those who did not are envisioned to validate its practical utility in enhancing surgical skills and preventing adverse events.

ABSTRACT. This paper presents, for the first time, a low melting point alloy (LMPA)-based variable stiffness soft everting robot. Everting robots can extend into difficult-to-access pathways, such as anatomical structures, by means of pressure-induced apical extension. The proposed system combines the benefits of soft-robot compliance with temperature-based stiffening to enable both navigation of such robot within the human body and high force exertion. The system uses a LMPA as both the actuation and stiffening medium, with emphasis on miniaturization and adaptability. The temperature of the LMPA is controlled to alternate between the stiff, solid state and the compliant, liquid state. The robot architecture follows our previous work, achieving steerability through a tendon-driven catheter embedded in its lumen. The robot is capable of sharp bends when steered and can apply shear forces of 2.9 N vs 0.16 N in its solid vs soft states at maximum deflection. This implies a stiffness ratio of 21.9 between the two states, which is 3-9 times higher than what has been previously reported for jamming-based stiffening approaches.

ABSTRACT. The teleoperated surgical training system suggested in this paper presents an economical and space-efficient desktop device designed to acquire manipulative training skills, aiding trainees in overcoming during medical procedures. The system includes a training console consisting of two master tool manipulators and patient side manipulators with 7 degrees of freedom. A point tracking method is used to replicate the spatial motion of the operator by the patient side manipulator, which requires the establishment of a kinematic model of both systems, based on which the inverse kinematics algorithms are derived. For approximation of the operator’s wrist rotation, an inertial measurement unit is used. The patient side manipulator's position in joint space is thereby regulated by a PID-controller in a negative feedback closed-loop control system. The performance of the teleoperated system is able to replicate motion input with a root-mean-square error for the three main axes of ±0.1604°, ±0.2527°, and ±0.6524 mm. Additionally, the proposed systems design and control is provided as an open-source project.

ABSTRACT. In this work, the Two Photon Polymerization technique is used to produce a waveguide that interfaces multi-core to single core optical fibers.This technique offers a fractional development cost compared to solutions such as optical fiber fanouts and can be potentially used along with cold splice connectors or heat shrinkable ferrules for alignment free interfacing. Additionally, the technique offers great waveguide design flexibility, which can enable both fan-in and fan-out designs.As a result better and more affordable laparoscopic sensing instruments with multi-axes sensing capabilities in the size of one optical fiber are enabled by this technology.

ABSTRACT. Simulation-based training plays a crucial role in enhancing patient safety by providing healthcare staff with realistic and standardized experiences. This study introduces a novel anatomically realistic knee simulator developed for standard and robotic knee arthroplasty. The simulator incorporates bones, ligaments, muscles, and skin, creating a comprehensive training platform. Mechanical tests on ligaments demonstrated comparable elastic moduli to real ligaments. Two surgical sessions, involving traditional and robotic knee arthroplasty, were conducted with residents and experts. A Likert questionnaire gauged face and content validity, revealing a consensus on anatomical structure and instrumentation feedback. Results demonstrated the simulator's effectiveness in knee arthroplasty training, with participants unanimously acknowledging its usefulness for standard and robotic knee arthroplasty. The discussion emphasizes the simulator's potential for active participation in learning outside the operating room. Future research aims to optimize 3D printing and develop a comprehensive training curriculum, including frontal lessons, cadaver, and phantom trials.

ABSTRACT. Various visuotactile sensors showed potential in capturing high resolution tactile information and contact measurements. However, there is minimal study on the development of a visuotactile sensor that captures multiple physical properties. We developed a visuotactile sensor, named OmniSense, that incorporates all the sensors' functionalities to completely sense the trifecta of tactile information - force, texture, and temperature using one sensor. The development of the hardware consists of both the electronics - camera, LED lights, and non-electronics parts - elastomer, support plate, and chassis. For OmniSense, we proposed a novel approach using gelatin plates as the elastomer’s material. Unlike traditional elastomers, gelatin plates are non-toxic and biodegradable. Subsequently, five different thermochromic pigments with different temperature thresholds were used: 15, 22, 31, 38, and 60 °C, colored yellow, light blue, magenta, royal blue, and orange, respectively to showcase the sensor’s reaction to various temperatures. We successfully developed a visuotactile sensor capable of sensing the trifecta of tactile information – force, texture, and temperature on one elastomer slab. In this research new design considerations and functionalities were achieved without sacrificing the quality of results as opposed to conventional sensors. In conclusion, given the high retrographic image production, it is also recommended to apply the use of the sensor in the field of medicine, specifically, in detecting lumps and various external conditions.

ABSTRACT. Surgery has undergone remarkable advancements in recent years, emphasizing the improvement of overall quality and the minimization of the impact of procedures on patients. The shift from traditional open-access approaches to minimally invasive surgery (MIS) has been significant, presenting undeniable advantages. However, challenges persist in adapting conventional surgical instruments for accuracy and miniaturization. This study addresses these challenges by proposing an origami-based tool to advance MIS, focusing on the development of an innovative gripper designed to overcome limitations in traditional surgical tools. The study emphasizes the creation of an origami-based design using rapid prototyping and additive manufacturing techniques. The gripper's mechanical characterization is conducted to assess its functionality and performance, showcasing its adaptability, potential miniaturization and increased flexibility.

ABSTRACT. We present a design optimization approach of a novel soft robotic manipulator that can navigate the lateral ventricle to evacuate bleeding inside the brain during intraventricular hemorrhage. It aims to reduce force exertion on brain tissue and provides a new access point to the posterior part of the lateral ventricle. The approach includes the parameterization of a cost function customized for this inextensible soft manipulator based on the piecewise constant curvature kinematics model. Anatomical data from a group of 40 patients was used to evaluate the optimal design. The numerical results suggest optimal design parameters which include the number of segments and length of segments as well as the range of motion required to fabricate the soft manipulator.

ABSTRACT. Concentric tube robots (CTRs) have shown promise in enhancing the dexterity of min-imally invasive surgical instruments while maintaining a small diameter. However, certain tube configurations lead to instabilities due to torsional wind-up during rota-tion, resulting in sudden snapping movements. Previous research has addressed this issue by maintaining torsional rigidity while reducing bending stiffness through aniso-tropic cutouts along the tubes. Nonetheless, some parts of the workspace remain dif-ficult to access. This paper revisits the concept of shape-locked CTRs, employing tube cross-sections shaped as regular polygons with n edges to prevent unintended rotation. Unlike pre-vious approaches, these tubes can still rotate in discrete steps if willingly subjected to sufficient torque. A two-tube CTR with an octagonal cross-section demonstrates eight discrete tip positions, setting up a discrete but uniform workspace. The study aims to investigate whether polygonal CTRs offer more uniform coverage of the workspace compared to annular CTRs. Six CTRs were manufactured from polyamide, three with an annular cross-section and three with an octagonal shape. The difference in tip rotation angles between inner and outer tube, i.e. torsional wind-up was recorded for both annular and shape-locked CTRs. Even if all sets of polygonal CTRs revealed wind-up, including the straight one, the results of the slightly curved CTR showed clear step-wise tip rotation, indicating that this method allows entering previously unstable regions of the workspace. These preliminary results can be fol-lowed up by studies of material and geometric parameters in order to reach discrete steps in a reliable way. The successful implementation of shape-locking could offer a safe and cost-effective approach for CTRs in everyday clinical use.

ABSTRACT. A non-invasive method of characterising bowel lesions using a two-stage machine learning (ML) procedure and a self-propelled robotic capsule has been proposed and investigated. As the capsule travels and encounters lesions in the lumen, its exhibited dynamics are envisaged to vary significantly and in correspondence to the biomechanical properties of encountered lesions. Measurable capsule dynamics such as its displacement signals have been acquired and processed for features that could be indicative of changes in the biomechanical property of bowel tissues such as stiffness (E). In the first stage ML, multi-layer perceptron (MLP) and support vector regression (SVR) were trained to predict E-values from the processed features. In the second stage, unsupervised K-means clustering is used to group the lesions into clusters of high intra-cluster similarities but low inter-cluster similarities using the MLP and SVR predicted E-values. The method achieved greater than 97 % clustering accuracies for both simulation and experimental data, thus providing a new modality to biopsy procedure and early cancer detection in the bowel.

ABSTRACT. With the capability of providing images of suspicious lesions inside soft tissues including the prostate, brain, and breast, Magnetic Resonance Imaging (MRI) has been widely used for cancer diagnosis and treatment. Traditional methods of cancer treatment require physicians to site a needle into the target area for biopsy, ablation, or brachytherapy. However, this has potential disadvantages including low accuracy, long procedure and postoperative recovery time, and low detection rates. In contrast, the utilisation of robots that can work in the Magnetic Resonance (MR) environment enhances MR-guided operations. Utilising high-resolution MR images, targeting accuracy can be improved, with detection rates increased significantly. However, there remain technical challenges to the deployment of robots in MRI scanners. Due to the strong magnetic field generated, ferromagnetic materials are prohibited from use, and with only limited use of paramagnetic materials, imposing additional requirements on the materials used for the robot. Several MR conditional robots have been proposed. Owing to the complicated structure and power transfer system, their large size limits application within the narrow closed bore. As such, this study proposes a new robot that has a compact size, allowing it to be easily placed within the MRI bore. The pneumatic actuators used are inherently MR-safe. With four degrees of freedom (DoFs), the needle can be inserted into the target point at various orientations.

ABSTRACT. Tendon driven continuum robotic tools for video assisted thoracoscopic surgery have exciting benefits in terms of their dexterity and navigability over existing rigid surgical tools. However for these continuum robots to be used to remove portions of the lung, they must be able to cut and seal off sections of tissue with a surgical staple. In this work, we demonstrate the feasibility of a soft manipulator with the capability to stiffen its backbone in a curved state in order to increase its strength so that it can fire a staple. The stiffening capability is accomplished with integrated channels of Field's metal, an alloy that melts at 62° C. Changing the stiffness in this manner enables the manipulator to retain the benefits of a continuum robot while also being capable of performing tasks that require a level of strength that conventional continuum robots cannot withstand.

ABSTRACT. In wearable robotics, physical Human-Machine Interfaces (pHMIs) should be able to adapt to the continuous physiological changes of body parts in an active, ergonomic, and safe way, ensuring a stable and comfortable biomechanical coupling with the user. This is particularly urgent in limb prostheses, where the pHMI is constituted by the socket. Indeed, traditional sockets are rigid and passive structures, causing significant discomforts and dermatological problems for patients, ultimately leading to device abandonment. Recent works indicate that 44% of upper limb amputees abandon their prostheses due to residual limb discomfort or pain, especially trans-humeral amputees. In this work, a smart trans-humeral socket is proposed. It integrates soft pneumatic actuators, a sensorized prosthetic liner, a wearable control unit, and a mobile app to enable both open- and closed-loop adaptation to residual limb volume changes, over time.

ABSTRACT. Robot-assisted minimally invasive surgery has gained prominence in various medical disciplines, necessitating the development of compact surgical tools with alternative actuation methods to address size constraints and minimize tissue trauma. This paper introduces an innovative forceps design utilizing magnetic actuation and twisted string actuators (TSAs) to achieve high force output in a smaller form factor.

The proposed forceps design exhibits a 3.25-fold reduction in length compared to previous iterations while maintaining a similar blocking force of 1.05N. This advancement enhances clinical feasibility, allowing for articulate tool manipulation within confined spaces. The tool's design, operating principle, magnetic and TSA models, and mechanical testing are presented. The system consists of an electromagnetic navigation system that generates a uniform rotating magnetic field, activating an internal permanent magnet within the forceps and twisted strings for force transmission.

Mechanical testing includes evaluating maximum blocking force, working blocking force range, and step-out frequency. Results indicate a maximum blocking force of 1.05 N, surpassing the average force required for neurosurgical procedures. The tool demonstrates rapid finger closure with a speed of 20.83 mm/s at a magnetic field strength of 14 mT and a frequency of 100 Hz.

Clinical feasibility is demonstrated through ex-vivo porcine brain tissue biopsy and in-vivo neurosurgical procedure using a concentric tube robot system. The integrated tool showcases proficient tissue manipulation, emphasizing its potential for practical clinical applications. The reduced tool length enables seamless integration into a robot-assisted surgical environment.

This tool represents the significance of using TSA in magnetically actuated surgical tools for stronger yet minimally invasive interventions. Future work includes enhancing tool reach, dexterity, and clinical maneuverability by incorporating a wrist and bi-manual tool actuation. This innovative forceps design demonstrates the potential for magnetic robot-assisted surgical procedures, highlighting the use of magnetic and TSA technologies for improved clinical outcomes.

ABSTRACT. Magnetically actuated Continuum Robots (MCRs) hold tremendous potential for miniaturization, offering the ability to navigate safely through tortuous pathways in various surgical interventions, including bronchoscopy, neurological procedures, and pancreatic surgeries. Despite their promising applications, a notable challenge arises during the removal of tissues post-ablation or foreign bodies impeding proper organism function, such as bile duct obstructions.

To address this limitation, this paper explores a hybrid design that amalgamates the benefits of MCRs with a millimetric tendon-actuated compliant gripper. In this innovative design, a MCR is strategically controlled to reach the targeted location, while a distal tendon-actuated compliant gripper is employed for precise target collection. This abstract delves into the dimensioning of the gripper concerning the stiffness of the MCR and investigates the effective workspace in correlation with the MCR's design.

ABSTRACT. Open spina bifida (OSB) is a spinal defect seen in developing fetuses. An in-utero approach to repair has improved outcomes and reduced risk of comorbidities in both mother and baby. To minimize the invasive impact, surgeons are investigating an in-utero robotic approach which presents the need for a simulator to enable surgeon training and planning. The major contributions of this paper are: An open-source dynamic simulator of the Da Vinci Xi Robotic Surgical System 2. A realistic virtual model of OSB 3. An integrated fetal robotics surgical simulator that allows surgeons to practice a simulated OSB repair.

ABSTRACT. Pedicle screw placement is a treatment for spinal diseases, but its success hinges on accurate placement to avoid pedicle breaches and nerve damage. The smart ball-tip feeler shortens the surgical time and enhances the accuracy of screw placement. Combining a load cell and an IMU, the LSTM-CNN based framework could accurately distinguish the breach and non-breach. Although this proposed ball-tip feeler is a proof-of-concept, it demonstrates a promising potential to be applied in clinical scenarios as low-cost and user-friendly surgical instrumentation.