Controlling and powering a fully implantable artificial pancreas refillable by ingestible pills.

Over the past decade, there has been a growing interest in the development of an artificial pancreas for intraperitoneal insulin delivery. Intraperitoneal implantable pumps guarantee more physiological glycemic control than subcutaneous wearable ones, for the treatment of type 1 diabetes. In this work, a fully implantable artificial pancreas refillable by ingestible pills is presented. In particular, solutions enabling the communication between the implanted pump and external user interfaces and novel control algorithms to intraperitoneally release an adequate amount of insulin based on glycemic data are shown. In addition, the powering and the wireless battery recharging are addressed. Specifically, the design and optimization of a customized transcutaneous energy transfer with two independent wireless channels are presented. The system was tested in terms of recharging efficacy, possible temperature rise within the body, during the recharging process and reliability of the wireless connection in the air and in the presence of ex vivo tissues.Clinical Relevance- This work aims to improve the control, battery recharging, and wireless communication of a fully implantable artificial pancreas for type 1 diabetes treatment.

Flipping food during grilling tasks, a dataset of utensils kinematics and dynamics, food pose and subject gaze.

This paper presents a multivariate dataset of 2866 food flipping movements, performed by 4 chefs and 5 home cooks, with different grilled food and two utensils (spatula and tweezers). The 3D trajectories of strategic points in the utensils were tracked using optoelectronic motion capture. The pinching force of the tweezers, the bending force and torsion torque of the spatula were also recorded, as well as videos and the subject gaze. These data were collected using a custom experimental setup that allowed the execution of flipping movements with freshly cooked food, without having the sensors near the dangerous cooking area. Complementary, the 2D position of food was computed from the videos. The action of flipping food is, indeed, gaining the attention of both researchers and manufacturers of foodservice technology. The reported dataset contains valuable measurements (1) to characterize and model flipping movements as performed by humans, (2) to develop bio-inspired methods to control a cooking robot, or (3) to study new algorithms for human actions recognition.

A Novel Biomimetic Compliant Structural Skin Based on Composite Materials for Biorobotics Applications.

Biorobotics is increasingly attracting engineers worldwide, due to the high impact this field can have on the society. Biorobotics aims at imitating or taking inspiration from mechanisms and strategies evolved by animals, including their locomotion abilities in real scenarios, such as swimming, running, crawling, and flying. However, the development of skin-mimicking structures, allowing protection without hindering artifacts' movements, has been rarely addressed. Skin-mimicking structures play a key role for biomimetic robots that have to move in unstructured environments. Currently most of the skin used for robots in engineering adopts soft materials or bellow structures to enable both structural deformation and protection. However, the elastic nature of the former can produce support failure and increasing strain with deformation, while the humpy surface of the latter reduces the interactive performance with the environment. Herein, we designed a novel compliant structure for biorobots' skin, fabricated through a special configuration of both soft and rigid materials to reproduce attributes provided by natural epithelial structures. The presented skin has a simple fabrication process, as well as it is cost effective. The structure of this skin includes a thin conical shape where rigid iron rings are wrapped by soft polyester fabrics, allowing a theoretically zero elastic modulus when bended and stretched. The dimension of fabrics was specified to allow rigid rings having a certain range of free rotation and translation. The possibility of free bending and stretching of the structure was implemented by overcoming low sliding friction of adjacent rings. To empirically test the effectiveness of the proposed structure, a model, including 20 segments, was also fabricated. Experimental results from the bending tests, both in aerial and underwater environments, as well as from the folding tests, demonstrated the successful performance of the skin prototype in terms of low resistance and energy consumption. Finally, the proposed highly compliant structural skin was mounted and tested on a fish robot previously developed by authors, to further show its effectiveness.

Five years of Science Robotics.

Looking back at the last 5 years of Science Robotics and looking forward to the next 5.

A Novel Capacitive Measurement Device for Longitudinal Monitoring of Bone Fracture Healing.

The healing process of surgically-stabilised long bone fractures depends on two main factors: (a) the assessment of implant stability, and (b) the knowledge of bone callus stiffness. Currently, X-rays are the main diagnostic tool used for the assessment of bone fractures. However, they are considered unsafe, and the interpretation of the clinical results is highly subjective, depending on the clinician's experience. Hence, there is the need for objective, non-invasive and repeatable methods to allow a longitudinal assessment of implant stability and bone callus stiffness. In this work, we propose a compact and scalable system, based on capacitive sensor technology, able to measure, quantitatively, the relative pins displacements in bone fractures treated with external fixators. The measurement device proved to be easily integrable with the external fixator pins. Smart arrangements of the sensor units were exploited to discriminate relative movements of the external pins in the 3D space with a resolution of 0.5 mm and 0.5°. The proposed capacitive technology was able to detect all of the expected movements of the external pins in the 3D space, providing information on implant stability and bone callus stiffness.

A fully implantable device for intraperitoneal drug delivery refilled by ingestible capsules.

Creating fully implantable robots that replace or restore physiological processes is a great challenge in medical robotics. Restoring blood glucose homeostasis in patients with type 1 diabetes is particularly interesting in this sense. Intraperitoneal insulin delivery could revolutionize type 1 diabetes treatment. At present, the intraperitoneal route is little used because it relies on accessing ports connecting intraperitoneal catheters to external reservoirs. Drug-loaded pills transported across the digestive system to refill an implantable reservoir in a minimally invasive fashion could open new possibilities in intraperitoneal delivery. Here, we describe PILLSID (PILl-refiLled implanted System for Intraperitoneal Delivery), a fully implantable robotic device refillable through ingestible magnetic pills carrying drugs. Once refilled, the device acts as a programmable microinfusion system for precise intraperitoneal delivery. The robotic device is grounded on a combination of magnetic switchable components, miniaturized mechatronic elements, a wireless powering system, and a control unit to implement the refilling and control the infusion processes. In this study, we describe the PILLSID prototyping. The device key blocks are validated as single components and within the integrated device at the preclinical level. We demonstrate that the refilling mechanism works efficiently in vivo and that the blood glucose level can be safely regulated in diabetic swine. The device weights 165 grams and is 78 millimeters by 63 millimeters by 35 millimeters, comparable with commercial implantable devices yet overcoming the urgent critical issues related to reservoir refilling and powering.

Endoluminal Motion Recognition of a Magnetically-Guided Capsule Endoscope Based on Capsule-Tissue Interaction Force.

A magnetically-guided capsule endoscope, embedding flexible force sensors, is designed to measure the capsule-tissue interaction force. The flexible force sensor is composed of eight force-sensitive elements surrounding the internal permanent magnet (IPM). The control of interaction force acting on the intestinal wall can reduce patient's discomfort and maintain the magnetic coupling between the external permanent magnet (EPM) and the IPM during capsule navigation. A flexible force sensor can achieve this control. In particular, by analyzing the signals of the force sensitive elements, we propose a method to recognize the status of the motion of the magnetic capsule, and provide corresponding formulas to evaluate whether the magnetic capsule follows the motion of the external driving magnet. Accuracy of the motion recognition in Ex Vivo tests reached 94% when the EPM was translated along the longitudinal axis. In addition, a method is proposed to realign the EPM and the IPM before the loss of their magnetic coupling. Its translational error, rotational error, and runtime are 7.04 ± 0.71 mm, 3.13 ± 0.47∘, and 11.4 ± 0.39 s, respectively. Finally, a control strategy is proposed to prevent the magnetic capsule endoscope from losing control during the magnetically-guided capsule colonoscopy.

Combating COVID-19-The role of robotics in managing public health and infectious diseases.

COVID-19 may drive sustained research in robotics to address risks of infectious diseases.

Frontiers of Robotic Gastroscopy: A Comprehensive Review of Robotic Gastroscopes and Technologies.

Upper gastrointestinal (UGI) tract pathology is common worldwide. With recent advancements in robotics, innovative diagnostic and treatment devices have been developed and several translational attempts made. This review paper aims to provide a highly pictorial critical review of robotic gastroscopes, so that clinicians and researchers can obtain a swift and comprehensive overview of key technologies and challenges. Therefore, the paper presents robotic gastroscopes, either commercial or at a progressed technology readiness level. Among them, we show tethered and wireless gastroscopes, as well as devices aimed for UGI surgery. The technological features of these instruments, as well as their clinical adoption and performance, are described and compared. Although the existing endoscopic devices have thus far provided substantial improvements in the effectiveness of diagnosis and treatment, there are certain aspects that represent unwavering predicaments of the current gastroenterology practice. A detailed list includes difficulties and risks, such as transmission of communicable diseases (e.g., COVID-19) due to the doctor-patient proximity, unchanged learning curves, variable detection rates, procedure-related adverse events, endoscopists' and nurses' burnouts, limited human and/or material resources, and patients' preferences to choose non-invasive options that further interfere with the successful implementation and adoption of routine screening. The combination of robotics and artificial intelligence, as well as remote telehealth endoscopy services, are also discussed, as viable solutions to improve existing platforms for diagnosis and treatment are emerging.

Robotic-Assisted Colonoscopy Platform with a Magnetically-Actuated Soft-Tethered Capsule.

Background and Aims: Colorectal cancer (CRC) is a major cause of morbidity and mortality worldwide. Despite offering a prime paradigm for screening, CRC screening is often hampered by invasiveness. Endoo is a potentially painless colonoscopy method with an active locomotion tethered capsule offering diagnostic and therapeutic capabilities. Materials and Methods: The Endoo system comprises a soft-tethered capsule, which embeds a permanent magnet controlled by an external robot equipped with a second permanent magnet. Capsule navigation is achieved via closed-loop interaction between the two magnets. Ex-vivo tests were conducted by endoscopy experts and trainees to evaluate the basic key features, usability, and compliance in comparison with conventional colonoscopy (CC) in feasibility and pilot studies. Results: Endoo showed a 100% success rate in operating channel and target approach tests. Progression of the capsule was feasible and repeatable. The magnetic link was lost an average of 1.28 times per complete procedure but was restored in 100% of cases. The peak value of interaction forces was higher in the CC group than the Endoo group (4.12N vs. 1.17N). The cumulative interaction forces over time were higher in the CC group than the Endoo group between the splenic flexure and mid-transverse colon (16.53Ns vs. 1.67Ns, p < 0.001), as well as between the hepatic flexure and cecum (28.77Ns vs. 2.47Ns, p = 0.005). The polyp detection rates were comparable between groups (9.1 ± 0.9% vs. 8.7 ± 0.9%, CC and Endoo respectively, per procedure). Robotic colonoscopies were completed in 67% of the procedures performed with Endoo (53% experts and 100% trainees). Conclusions: Endoo allows smoother navigation than CC and possesses comparable features. Although further research is needed, magnetic capsule colonoscopy demonstrated promising results compared to CC.

Photometric Stereo-Based Depth Map Reconstruction for Monocular Capsule Endoscopy.

The capsule endoscopy robot can only use monocular vision due to the dimensional limit. To improve the depth perception of the monocular capsule endoscopy robot, this paper proposes a photometric stereo-based depth map reconstruction method. First, based on the characteristics of the capsule endoscopy robot system, a photometric stereo framework is established. Then, by combining the specular property and Lambertian property of the object surface, the depth of the specular highlight point is estimated, and the depth map of the whole object surface is reconstructed by a forward upwind scheme. To evaluate the precision of the depth estimation of the specular highlight region and the depth map reconstruction of the object surface, simulations and experiments are implemented with synthetic images and pig colon tissue, respectively. The results of the simulations and experiments show that the proposed method provides good precision for depth map reconstruction in monocular capsule endoscopy.

Prediction of Passive Torque on Human Shoulder Joint Based on BPANN.

In upper limb rehabilitation training by exploiting robotic devices, the qualitative or quantitative assessment of human active effort is conducive to altering the robot control parameters to offer the patients appropriate assistance, which is considered an effective rehabilitation strategy termed as assist-as-needed. Since active effort of a patient is changeable for the conscious or unconscious behavior, it is considered to be more feasible to determine the distributions of the passive resistance of the patient's joints versus the joint angle in advance, which can be adopted to assess the active behavior of patients combined with the measurement of robotic sensors. However, the overintensive measurements can impose a burden on patients. Accordingly, a prediction method of shoulder joint passive torque based on a Backpropagation neural network (BPANN) was proposed in the present study to expand the passive torque distribution of the shoulder joint of a patient with less measurement data. The experiments recruiting three adult male subjects were conducted, and the results revealed that the BPANN exhibits high prediction accurate for each direction shoulder passive torque. The results revealed that the BPANN can learn the nonlinear relationship between the passive torque and the position of the shoulder joint and can make an accurate prediction without the need to build a force distribution function in advance, making it possible to draw up an assist-as-needed strategy with high accuracy while reducing the measurement burden of patients and physiotherapists.

Frontiers of Robotic Colonoscopy: A Comprehensive Review of Robotic Colonoscopes and Technologies.

Flexible colonoscopy remains the prime mean of screening for colorectal cancer (CRC) and the gold standard of all population-based screening pathways around the world. Almost 60% of CRC deaths could be prevented with screening. However, colonoscopy attendance rates are affected by discomfort, fear of pain and embarrassment or loss of control during the procedure. Moreover, the emergence and global thread of new communicable diseases might seriously affect the functioning of contemporary centres performing gastrointestinal endoscopy. Innovative solutions are needed: artificial intelligence (AI) and physical robotics will drastically contribute for the future of the healthcare services. The translation of robotic technologies from traditional surgery to minimally invasive endoscopic interventions is an emerging field, mainly challenged by the tough requirements for miniaturization. Pioneering approaches for robotic colonoscopy have been reported in the nineties, with the appearance of inchworm-like devices. Since then, robotic colonoscopes with assistive functionalities have become commercially available. Research prototypes promise enhanced accessibility and flexibility for future therapeutic interventions, even via autonomous or robotic-assisted agents, such as robotic capsules. Furthermore, the pairing of such endoscopic systems with AI-enabled image analysis and recognition methods promises enhanced diagnostic yield. By assembling a multidisciplinary team of engineers and endoscopists, the paper aims to provide a contemporary and highly-pictorial critical review for robotic colonoscopes, hence providing clinicians and researchers with a glimpse of the major changes and challenges that lie ahead.

Permeable hollow 3D tissue-like constructs engineered by on-chip hydrodynamic-driven assembly of multicellular hierarchical micromodules.

Engineered three-dimensional (3D) microtissues that recapitulate in vivo tissue morphology and microvessel lumens have shown significant potential in drug screening and regenerative medicine. Although microfluidic-based techniques have been developed for bottom-up assembly of 3D tissue models, the spatial organization of heterogeneous micromodules into tissue-specific 3D constructs with embedded microvessels remains challenging. Inspired by a hydrodynamic-based classic game which stacks rings in water through the flow, a facile strategy is proposed for effective assembly of heterogeneous hierarchical micromodules with a central hole, into permeable hollow 3D tissue-like constructs through hydrodynamic interaction in a versatile microfluidic chip. The micromodules are fabricated by in situ multi-step photo-crosslinking of cell-laden hydrogels with different mechanical properties to give the high fidelity. With the hydrodynamic interaction derived from the discontinuous circulating flow, the micromodules are spatially organized layer-by-layer to form a 3D construct with a microvessel-like lumen. As an example, a ten-layered liver lobule-like construct containing inner radial-like poly(ethylene glycol) diacrylate (PEGDA) structure with hepatocytes and outer hexagonal gelatin methacrylate (GelMA) structure with endothelial cells are assembled in 2 min. During 10 days of co-culture, cells maintain high viability and proliferated along with the composite lobule-like morphology. The 3D construct owns a central lumen, which allows perfusion culture to promote albumin secretion. We anticipate that this microassembly strategy can be used to fabricate vascularized 3D tissues with various physiological morphologies as alternatives for biomedical research applications. STATEMENT OF SIGNIFICANCE: Microfluidic-based assembly is an attractive approach for the fabrication of 3D tissue models using cell-laden hydrogel microstructures with single mechanical stability. However, native tissues are complex 3D structures with indispensable vessels and multiple mechanical properties, which is still challenging to recreate. This study proposed a novel strategy to fabricate tissue-like 3D constructs with embedded lumen through hydrodynamic interaction using multicellular micromodules with hierarchical mechanical properties. The resultant hollow 3D constructs allow perfusion co-culture to enhance cell activity. This strategy relies on a simple and facile microfluidic chip to fabricate various 3D tissue-like constructs with hierarchical mechanical properties and permeable lumen, which can potentially be used as in vitro perfusion models for biomedical research.

Visual-Based Defect Detection and Classification Approaches for Industrial Applications-A SURVEY.

This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles. In the first part of the paper, we present a general taxonomy of the different defects that fall in two classes: visible (e.g., scratches, shape error, etc.) and palpable (e.g., crack, bump, etc.) defects. Then, we describe artificial visual processing techniques that are aimed at understanding of the captured scenery in a mathematical/logical way. We continue with a survey of textural defect detection based on statistical, structural and other approaches. Finally, we report the state of the art for approaching the detection and classification of defects through supervised and non-supervised classifiers and deep learning.

Template-based fabrication of spatially organized 3D bioactive constructs using magnetic low-concentration gelation methacrylate (GelMA) microfibers.

Low concentrations of gelatin methacrylate (GelMA) microfibers are more favorable for cellular activity compared with high concentrations. However, applying low-concentration GelMA microfibers as building blocks for higher-order cellular assembly remains challenging owing to their poor mechanical properties. Herein, we report a new template-based method to solve this problem. GelMA microfibers (5%, w/v) containing magnetic nanoparticles were synthesized by a microfluidic spinning method. A 9 × 9 micropillar array surrounded by a magnetic substrate was constructed to form 8 × 8 microgaps arranged in a crisscross pattern as a magnetic template. In DMEM solution, magnetic attraction facilitated efficient arrangement of the microfibers according to the template with micron assembly accuracy, with a microgrid-like construct (microGC) generated after removing all micropillars. MicroGCs were shown to effectively support the activities of surface seeded or encapsulated cells and be flexibly constructed with various organized spatial patterns. Owing to the low mechanical property requirements of assembled microfibers and the easy-to-implement operation, the proposed method provides a versatile pathway for the assembly of various microfluidic spun microfibers. Furthermore, the resulting 3D microgrid-like cellular constructs with organized spatiotemporal composition offer a convenient platform for the study of tissue engineering.

Optical and Electromagnetic Tracking Systems for Biomedical Applications: A Critical Review on Potentialities and Limitations.

Optical and electromagnetic tracking systems represent the two main technologies integrated into commercially-available surgical navigators for computer-assisted image-guided surgery so far. Optical Tracking Systems (OTSs) work within the optical spectrum to track the position and orientation, i.e., pose of target surgical instruments. OTSs are characterized by high accuracy and robustness to environmental conditions. The main limitation of OTSs is the need of a direct line-of-sight between the optical markers and the camera sensor, rigidly fixed into the operating theatre. Electromagnetic Tracking Systems (EMTSs) use electromagnetic field generator to detect the pose of electromagnetic sensors. EMTSs do not require such a direct line-of-sight, however the presence of metal or ferromagnetic sources in the operating workspace can significantly affect the measurement accuracy. The aim of the proposed review is to provide a complete and detailed overview of optical and electromagnetic tracking systems, including working principles, source of error and validation protocols. Moreover, commercial and research-oriented solutions, as well as clinical applications, are described for both technologies. Finally, a critical comparative analysis of the state of the art which highlights the potentialities and the limitations of each tracking system for a medical use is provided.

Correction: Fiorini, L., et al., Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data. Sensors 2017, 17, 1034.

A correction is presented to correct the section headings of Sections 5.1, 5.2, and 5.3 in[Sensors, 2017, 17, 1034].

Three-Dimensional Autofocusing Visual Feedback for Automated Rare Cells Sorting in Fluorescence Microscopy.

Sorting rare cells from heterogeneous mixtures makes a significant contribution to biological research and medical treatment. However, the performances of traditional methods are limited due to the time-consuming preparation, poor purity, and recovery rate. In this paper, we proposed a cell screening method based on the automated microrobotic aspirate-and-place strategy under fluorescence microscopy. A fast autofocusing visual feedback (FAVF) method is introduced for precise and real-time three-dimensional (3D) location. In the context of this method, the scalable correlation coefficient (SCC) matching is presented for planar locating cells with regions of interest (ROI) created for autofocusing. When the overlap occurs, target cells are separated by a segmentation algorithm. To meet the shallow depth of field (DOF) limitation of the microscope, the improved multiple depth from defocus (MDFD) algorithm is used for depth detection, taking 850 ms a time with an accuracy rate of 96.79%. The neighborhood search based algorithm is applied for the tracking of the micropipette. Finally, experiments of screening NIH/3T3 (mouse embryonic fibroblast) cells verifies the feasibility and validity of this method with an average speed of 5 cells/min, 95% purity, and 80% recovery rate. Moreover, such versatile functions as cell counting and injection, for example, could be achieved by this expandable system.

Tactile Decoding of Edge Orientation With Artificial Cuneate Neurons in Dynamic Conditions.

Generalization ability in tactile sensing for robotic manipulation is a prerequisite to effectively perform tasks in ever-changing environments. In particular, performing dynamic tactile perception is currently beyond the ability of robotic devices. A biomimetic approach to achieve this dexterity is to develop machines combining compliant robotic manipulators with neuroinspired architectures displaying computational adaptation. Here we demonstrate the feasibility of this approach for dynamic touch tasks experimented by integrating our sensing apparatus in a 6 degrees of freedom robotic arm via a soft wrist. We embodied in the system a model of spike-based neuromorphic encoding of tactile stimuli, emulating the discrimination properties of cuneate nucleus neurons based on pathways with differential delay lines. These strategies allowed the system to correctly perform a dynamic touch protocol of edge orientation recognition (ridges from 0 to 40°, with a step of 5°). Crucially, the task was robust to contact noise and was performed with high performance irrespectively of sensing conditions (sensing forces and velocities). These results are a step forward toward the development of robotic arms able to physically interact in real-world environments with tactile sensing.