In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of the right ventricle is challenging due to its highly complex shape and ill-defined borders. Hence, there is a need for new methods to handle such structure's geometrical and textural complexities, notably in the presence of pathologies such as Dilated Right Ventricle, Tricuspid Regurgitation, Arrhythmogenesis, Tetralogy of Fallot, and Inter-atrial Communication. The last MICCAI challenge on right ventricle segmentation was held in 2012 and included only 48 cases from a single clinical center. As part of the 12th Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2021), the M&Ms-2 challenge was organized to promote the interest of the research community around right ventricle segmentation in multi-disease, multi-view, and multi-center cardiac MRI. Three hundred sixty CMR cases, including short-axis and long-axis 4-chamber views, were collected from three Spanish hospitals using nine different scanners from three different vendors, and included a diverse set of right and left ventricle pathologies. The solutions provided by the participants show that nnU-Net achieved the best results overall. However, multi-view approaches were able to capture additional information, highlighting the need to integrate multiple cardiac diseases, views, scanners, and acquisition protocols to produce reliable automatic cardiac segmentation algorithms.

The need to create more viable soft sensors is increasing in tandem with the growing interest in soft robots. Several sensing methods, like capacitive stretch sensing and intrinsic capacitive self-sensing, have proven to be useful when controlling soft electro-hydraulic actuators, but are still problematic. This is due to challenges around high-voltage electronic interference or the inability to accurately sense the actuator at higher actuation frequencies. These issues are compounded when trying to sense and control the movement of a multiactuator system. To address these shortcomings, we describe a two-part magnetic sensing mechanism to measure the changes in displacement of an electro-hydraulic (HASEL) actuator. Our magnetic sensing mechanism can achieve high accuracy and precision for the HASEL actuator displacement range, and accurately tracks motion at actuation frequencies up to 30 Hz, while being robust to changes in ambient temperature and relative humidity. The high accuracy of the magnetic sensing mechanism is also further emphasized in the gripper demonstration. Using this sensing mechanism, we can detect submillimeter difference in the diameters of three tomatoes. Finally, we successfully perform closed-loop control of one folded HASEL actuator using the sensor, which is then scaled into a deformable tilting platform of six units (one HASEL actuator and one sensor) that control a desired end effector position in 3D space. This work demonstrates the first instance of sensing electro-hydraulic deformation using a magnetic sensing mechanism. The ability to more accurately and precisely sense and control HASEL actuators and similar soft actuators is necessary to improve the abilities of soft, robotic platforms.

Locomotion through rolling is attractive compared to other forms of locomotion thanks to uniform designs, high degree of mobility, dynamic stability, and self-recovery from collision. Despite previous efforts to design rolling soft systems, pneumatic and other soft actuators are often limited in terms of high-speed dynamics, system integration, and/or functionalities. Furthermore, mathematical description of the rolling dynamics for this type of robot and how the models can be used for speed control are often not mentioned. This article introduces a cylindrical-shaped shell-bulging rolling soft wheel that employs an array of 16 folded-HASEL actuators as a mean for improved rolling performance. The actuators represent the soft components with discrete forces that propel the wheel, whereas the wheel's frame is rigid but allows for smooth, continuous change in position and speed. We discuss the interplay between the electrical and mechanical design choices, the modeling of the wheel's hybrid (continuous and discrete) dynamic behavior, and the implementation of a model predictive controller (MPC) for the robot's speed. With the balance of several design factors, we show the wheel's ability to carry integrated hardware with a maximum rolling speed at 0.7 m/s (or 2.2 body lengths per second), despite its total weight of 979 g, allowing the wheel to outperform the existing rolling soft wheels with comparable weights and sizes. We also show that the MPC enables the wheel to accelerate and leverage its inherent braking capability to reach desired speeds—a critical function that did not exist in previous rolling soft systems.

With significant progress being made toward improving endoscope technology such as capsule endoscopy and robotic endoscopy, the development of advanced strategies for manipulating, controlling, and more generally, easing the accessibility of these devices for physicians is an important next step. This article presents an autonomous navigation strategy for use in endoscopy, utilizing a state-dependent region estimation approach to allow for multimodal control design. This region estimator is evaluated for its accuracy in predicting yaw angle of the camera relative to the lumen center, and for estimating the location of the camera based on overall haustra morphology within the colon. To assess the utility of this region estimator, multimodal control is used to allow for autonomous navigation of the Endoculus, a robotic capsule endoscope, within a benchtop, to-scale, simulated colon. The estimation approach is presented and tested, demonstrating successful tracking of fixed velocity rotations at speeds up to 40°/s and allowing for curve anticipation approximately 10 cm before entering a curved section of the simulator. Finally, the multimodal control strategy utilizing this estimator is tested within the simulator over a variety of anatomic configurations. This strategy proves successful for navigation in both straight sections of this simulator and in tightly curved sections as small as 8 cm radius of curvature, with average velocities reaching 2.61 cm/s in straight sections and 0.99 cm/s in curved sections.

This paper presents a new open-source dataset with ground truth position in a simulated colon environment to promote development of real-time feedback systems for physicians performing colonoscopies. Four systems (DSO, LSD-SLAM, SfMLearner, ORB-SLAM2) are tested on this dataset and their failures are analyzed. A data collection platform was fabricated and used to take the dataset in a colonoscopy training simulator that was affixed to a flat surface. The noise in the ground truth positional data induced from the metal in the data collection platform was then characterized and corrected. The Absolute Trajectory RMSE Error (ATE) and Relative Error (RE) metrics were performed on each of the sequences in the dataset for each of the Simultaneous Localization And Mapping (SLAM) systems. While these systems all had good performance in idealized conditions, more realistic conditions in the harder sequences caused them to produce poor results or fail completely. These failures will be a hindrance to physicians in a real-world scenario, so future systems made for this environment must be more robust to the difficulties found in the colon, even at the expense of trajectory accuracy. The authors believe that this is the first open-source dataset with groundtruth data displaying a simulated in vivo environment with active deformation, and that this is the first step toward achieving useful SLAM within the colon. The dataset is available at www.colorado.edu/lab/amtl/datasets.

Robotic capsule endoscopes (RCEs) are being widely investigated to improve the state of various endoscopy procedures. This article presents the novel design of a multi-DOF sensor-enabled RCE for colonoscopies (Endoculus) and evaluates porcine in vivo and ex vivo performance. The novelty of the design includes a custom “double-worm” drive that removes axial gear forces while reducing radial moments, and the full parameterization of gear geometries allows for size minimization via an optimization routine over design constraints. Two independently controlled motors drive micro-pillared treads above and below the device allowing for two-degrees of freedom (2-DOF) skid-steering, even in a collapsed lumen. The Endoculus contains all functionality of a traditional endoscope: a camera, adjustable light emitting diodes (LEDs), channels for insufflation and irrigation, and a tool port for endoscopy instruments (e.g., forceps, snares, etc.). Additionally, the Endoculus carries an inertial measurement unit, magnetometer, motor encoders, and motor current sensors to aid in future autonomy strategies. Porcine surgical evaluation demonstrated locomotion up to 40 mm/s on the colon mucosa, 2-DOF steering, the ability to traverse haustral folds, and functionality of endoscopy tools. This platform will enable future validation of feedback control, localization, and mapping algorithms in the unconventional in vivo environment.

Capsule endoscopes have gained popularity over the last decade as minimally invasive devices for diagnosing gastrointestinal abnormalities such as colorectal cancer. While this technology offers a less invasive and more convenient alternative to traditional scopes, these capsules are only able to provide observational capabilities due to their passive nature. With the addition of a reliable mobility system and a real-time navigation system, capsule endoscopes could transform from observational devices into active surgical tools, offering biopsy and therapeutic capabilities and even autonomous navigation in a single minimally invasive device. In this work, a vision system is developed to allow for autonomous lumen center tracking and haustral fold identification and tracking during colonoscopy. This system is tested for its ability to accurately identify and track multiple haustral folds across many frames in both simulated and in vivo video, and the lumen center tracking is tested onboard a robotic endoscope platform (REP) within an active simulator to demonstrate autonomous navigation. In addition, real-time localization is demonstrated using open source ORB-SLAM2. The vision system successfully identified 95.6% of Haustral folds in simulator frames and 70.6% in in vivo frames and false positives occurred in less than 1% of frames. The center tracking algorithm showed in vivo center estimates within a mean error of 6.6% of physician estimates and allowed for the REP to traverse 2 m of the active simulator in 6 minutes without intervention.

This paper describes a system identification method and the development of a closed-loop controller for a Hydraulically Amplified Self-healing Electrostatic (HASEL) actuator. Our efforts focus on developing a reliable and consistent way to identify system models for these soft robotic actuators using high-speed videography based motion tracking. Utilizing a mass-spring-damper model we are able to accurately capture the behavior of a HASEL actuator. We use the resulting plant model to design a Proportional-Integral controller that demonstrates improved closed-loop tracking and steady-state error performance.

Traditional colonoscopy requires highly trained personnel to be performed. Additionally, current devices may cause discomfort and carry the risk of perforating the bowel wall. In this paper, a soft three modular section robot is designed, modeled, controlled and tested. Each of the robotic sections has three degrees of freedom, one translation and two rotations. The robot uses a peristaltic motion to translate, inspired by the motion generated by the bowel. The robot uses nine independently controlled Shape Memory Alloy (SMA) springs as its actuators and a novel silicone rubber skin provides the passive recovery force to expand the springs to their original state. It also incorporates three air tubes, one for each section, to provide forced convection reducing the cooling time of the SMA springs. A parametric study on the skin curvature and thickness using Finite Element Analysis (FEA) is performed to maximize traction while providing enough recovery force. A multi-input multi-output (MIMO) controller based on fuzzy control is designed and implemented for each of the sections allowing the robot to achieve any orientation between −90° and +90° in both pitch and roll in less than 4 seconds with near zero steady state error. Both the peristaltic motion and the orientability of the robot are tested. The robot is able to perform a peristaltic motion with maximum speed of 4 mm/s (24 cm/min) and an average speed of 2.2 cm/min. Each section is also able to follow, with less than 2% overshoot and near zero steady-state error, periodic multi-input squared signals of 25° of amplitude.

Design is widely considered to be the central or distinguishing activity of engineering and yet it remains an insufficiently researched and understood topic. From the perspective of engineering education, where a "disconnect" between professional engineering practices and university-based practices is an oft-discussed limitation, the sparseness of research on professional engineering design is noteworthy. Specific representations of real engineering practices are necessary to inform attempts to prepare future engineers. The present study attends to the location of engineering design in different organizational settings, as a way of examining the nature of purported "disconnects" between professional engineering design practices and those taking place in the undergraduate curriculum. Our core methodology is that of cognitive ethnography, which examines how cognitive tasks, in our case design, are accomplished within "functional systems" constituted of heterogeneous elements, both human and nonhuman. Our focus is on "how the work of the organization" gets done through the process of design. This work in progress (WIP) paper explores the spatiotemporal organization of activity as a key aspect of the situatedness and heterogeneity of design work, and reports preliminary findings regarding important differences in how design is organized in different design settings.

Palpating tissues and organs to identify hidden tumors or to detect buried vessels is not a viable option in laparoscopic surgery due to lack of force feedback. So far, research toward restoring tactile and kinesthetic sensations in minimally invasive surgery has focused on the distal sensing element or on the proximal rendering of haptic cues. In this work we present a pilot study to assess the feasibility of wireless tissue palpation, where a magnetic device is deployed through a standard surgical trocar and operated to perform tissue palpation without requiring a dedicated entry port. The setup consists of a wireless intra-body device and an external robotic manipulator holding a load cell and a permanent magnet. Embedded in the wireless cylindrical device (12.7 mm in diameter and 27.5 mm in height) is a sensing module, a wireless microcontroller, a battery and a permanent magnet. This preliminary study assessed the precision in reconstructing the indentation depth based on magnetic field measurements at the wireless device (i.e., 0.1 mm accuracy). Experimental trials demonstrated the effectiveness of wireless vertical indentation in detecting the elastic modulus of three different silicone tissue simulators (elastic modulus ranging from 50 kPa to 93 kPa), showing a maximum relative error below 3%. Finally, wireless palpation was used to identify differences in tissue stiffness from a lump embedded into a porcine liver. The reported results have the potential to open a new paradigm in the field of palpation devices, where direct physical connection across the abdominal wall is no longer required.

In this work an overview of in vivo robotic capsule colonoscopy (RCC) is given, followed by the introduction of a mobility method for a RCC using micro-patterned polydimethylsiloxane (PDMS). The design of a four degree of freedom (DOF) automated traction measurement (ATM) platform for quantitative evaluation of the mobility method is presented. An empirical model for traction force as a function of slip ratio, robot speed and robot weight for micro-patterned PDMS on synthetic tissue is developed using data collected from the ATM platform. The model is then used to predict traction force at different speeds and weights, and is verified experimentally. The mean percent error between the empirical model and the data used to develop the model is 2.1% (min 0.051%, max 6.5%). The mean error between the traction force predicted by the model and the data used to verify the prediction is 5.9% (min 0.0035%, max 21%). The results from this study will play a key role in further RCC mobility system optimization going forward.

Long-term human space exploration will require contingencies for emergency medical procedures including some capability to perform surgery. The ability to perform minimally invasive surgery (MIS) would be an important capability. The use of small incisions reduces surgical risk, but also eliminates the ability of the surgeon to view and touch the surgical environment directly. Robotic surgery, or telerobotic surgery, may provide emergency surgical care in remote or harsh environments such as space flight, or extremely forward environments such as battlefields. However, because current surgical robots are large and require extensive support personnel, their implementation has remained limited in forward environments, and they would be difficult, or impossible, to use in space flight or on battlefields. This paper presents experimental analysis of miniature fixed-base and mobile in vivo robots to support MIS surgery in remote and harsh environments. The objective is to develop wireless imaging and task-assisting robots that can be placed inside the abdominal cavity during surgery. Such robots will provide surgical task assistance and enable an on-site or remote surgeon to view the surgical environment from multiple angles. This approach is applicable to long-duration space flight, battlefield situations, and for traditional medical centers and other remote surgical locations.

A mobile in vivo camera robot was developed to provide the ability for a single port biopsy procedure. Such a robot can be inserted into the abdominal cavity through a standard trocar. The surgeon controls the robot using visual feedback from the on-board camera. Measurements were made to identify the forces required to successfully biopsy in vivo tissue, including clamping and tearing forces. The robot design was developed around these parameters and the need to traverse the abdominal environment using specially designed wheels. This mobility allows the biopsy robot to move to the area of interest to sample specific tissues. The lead-screw linkage system that actuated the graspers allows for large force production through careful mechanical design. In vivo testing of this system in a porcine (pig) model has been successful. The robot is capable of traversing the entire in vivo abdominal environment and has successfully been used to biopsy hepatic tissue. In addition, experimental analysis of the biopsy mechanism shows good results towards more elaborate tissue manipulation in the future

Laparoscopy is abdominal surgery performed with long tools inserted through small incisions. The use of small incisions reduces patient trauma, but also eliminates the surgeon's ability to view and touch the surgical environment directly. These limitations generally restrict the application of laparoscopy to procedures less complex than those performed during open surgery. This paper presents a theoretical and experimental analysis of miniature, wheeled, in vivo robots to support laparoscopy. The objective is to develop a wireless mobile imaging robot that can be placed inside the abdominal cavity during surgery. Such robots will allow the surgeon to view the surgical environment from multiple angles. The motion of these in vivo robots will not be constrained by the insertion incisions. Simulation and experimental analyses have led to a wheel design that can attain good mobility performance in in vivo conditions