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Abstract Magnetically actuated miniature origami crawlers are capable of robust locomotion in confined environments but are limited to passive functionalities. Here, we propose a bistable origami crawler that can shape-morph to access two separate regimes of folding degrees of freedom that are separated by an energy barrier. Using the modified bistable V-fold origami crease pattern as the fundamental unit of the crawler, we incorporated internal permanent magnets to enable untethered shape-morphing. By modulating the orientation of the external magnetic field, the crawler can reconfigure between an undeployed locomotion state and a deployed load-bearing state. In the undeployed state, the crawler can deform to enable out-of-plane crawling for robust bi-directional locomotion and navigation in confined environments based on friction anisotropy. In the deployed state, the crawler can execute microneedle insertion in confined environments. Through this work, we demonstrated the advantage of incorporating bistability into origami mechanisms to expand their capabilities in space-constraint applications.

Abstract The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Abstract In robotic-assisted surgery (RAS), traditional surgical instruments without sensing capability cannot perceive accurate operational forces during the task, and such drawbacks can be largely intensified when sophisticated tasks involving flexible and slender arms with small end-effectors, such as in gastrointestinal endoscopic surgery (GES). In this study, we propose a microelectromechanical system (MEMS) piezoresistive 3-axial tactile sensor for GES forceps, which can intuitively provide surgeons with online force feedback during robotic surgery. The MEMS fabrication process facilitates sensor chips with miniaturized dimensions. The fully encapsulated tactile sensors can be effortlessly integrated into miniature GES forceps, which feature a slender diameter of just 3.5 mm and undergo meticulous calibration procedures via the least squares method. Through experiments, the sensor’s ability to accurately measure directional forces up to 1.2 N in the Z axis was validated, demonstrating an average relative error of only 1.18% compared with the full-scale output. The results indicate that this tactile sensor can provide effective 3-axial force sensing during surgical operations, such as grasping and pulling, and in ex vivo testing with a porcine stomach. The compact size, high precision, and integrability of the sensor establish solid foundations for clinical application in the operating theater.

Abstract Intraluminal epithelial abnormalities, potential precursors to significant conditions like cancer, necessitate early detection for improved prognosis. We present a motor-free telerobotic optical coherence tomography (OCT) endoscope that offers high-resolution intraluminal imaging and overcomes the limitations of traditional systems in navigating curved lumens. This system incorporates a compact magnetic rotor with a rotatable diametrically magnetized cylinder permanent magnet (RDPM) and a reflector, effectively mitigating thermal and electrical risks by utilizing an external magnetic field to maintain temperature increases below 0.5 °C and generated voltage under 0.02 mV. Additionally, a learning-based method corrects imaging distortions resulting from nonuniform rotational speeds. Demonstrating superior maneuverability, the device achieves steerable angles up to 110° and operates effectively in vivo, providing distortion-free 3D programmable imaging in mouse colons. This advancement represents a significant step towards guidewire-independent endomicroscopy, enhancing both safety and potential patient outcomes.

Origami exhibits the remarkable ability to transform into diverse shapes, including quadrilaterals, triangles, and more complex polygons. This unique property has inspired the integration of origami principles into engineering design, particularly in the development of foldable mechanisms. In the field of robotics, when combined with actuators, these foldable mechanisms are referred to as active origami. Origami-based mechanisms play a pivotal role as versatile end effectors or grippers, enabling them to accurately trace desired trajectories. The performance of these mechanisms heavily relies on their specific fold patterns. To shed light on their capabilities, this study focuses on five representative structures using spherical mechanisms: oriceps, Miura ori, MACIOR, and two hexagonal structures. To assess their potential, a comparative analysis is conducted, evaluating their kinematic and scaling performances. The analysis employs the “scaling factor” as a metric, which quantifies the mechanical advantage of these mechanisms. This metric aids in the selection of appropriate structures for various applications.

Older individuals are easily prone to chronic pain. Due to the complexity of chronic pain, most elderly often have difficulty expressing pain to others to seek assistance, especially those with Alzheimer’s disease (AD). The caregivers cannot instantly discover the patients’ pain condition and provide timely pain management. This project applies physiological signal sensing technology to help AD patients express the presence of pain non-verbally. We embed sensors on patients’ handkerchiefs to identify the patient’s abnormal physical activity when pain occurs. Next, we translate the physiological signal into qualitative light alert to send to caregivers and indicate the pain occurrence condition. Then, utilizing multi-sensory stimulation intervention, we create an electronic textile (e-textile) tool to help caregivers effectively support patients in pain. And thus to create a two-way pain communication between caregivers and the patients. Pain perception can be independent of subjective expressions and tangibly perceived by others through our textile prototype. The e-textile handkerchiefs also bring up a new guide to facilitate communication for caregivers when their patients. We contribute the design insights of building a bio-sensing and e-textile system with considering the pain communication needs, patients’ pain behaviors and preference of objects. Our e-textile system may contribute to pain communication bio-sensing tool design for special elderly groups, especially those with weakened cognition and communication abilities. We provide a new approach to dealing with the pain of AD patients for healthcare professionals.

In the robot-assisted minimally invasive surgery, if a collision occurs, the robot system program could be damaged, and normal tissues could be injured. To avoid collisions during surgery, a 3-dimensional collision avoidance method is proposed in this paper. The proposed method is predicated on the design of 3 strategic vectors: the collision-with-instrument-avoidance (CI) vector, the collision-with-tissues-avoidance (CT) vector, and the constrained-control (CC) vector. The CI vector demarcates 3 specific directions to forestall collision among the surgical instruments. The CT vector, on the other hand, comprises 2 components tailored to prevent inadvertent contact between the robot-controlled instrument and nontarget tissues. Meanwhile, the CC vector is introduced to guide the endpoint of the robot-controlled instrument toward the desired position, ensuring precision in its movements, in alignment with the surgical goals. Simulation results verify the proposed collision avoidance method for robot-assisted minimally invasive surgery. The code and data are available at https://github.com/cynerelee/collision-avoidance.

Robot-assisted technologies are being investigated to overcome the limitations of the current solutions for transoral surgeries, which suffer from constrained insertion ports, lengthy and indirect passageways, and narrow anatomical structures. This paper reviews distal dexterity mechanisms, variable stiffness mechanisms, and triangulation mechanisms, which are closely related to the specific technical challenges of transoral robotic surgery (TORS). According to the structure features in moving and orienting end effectors, the distal dexterity designs can be classified into 4 categories: serial mechanism, continuum mechanism, parallel mechanism, and hybrid mechanism. To ensure adequate adaptability, conformability, and safety, surgical robots must have high flexibility, which can be achieved by varying the stiffness. Variable stiffness (VS) mechanisms based on their working principles in TORS include phase-transition-based VS mechanism, jamming-based VS mechanism, and structure-based VS mechanism. Triangulations aim to obtain enough workspace and create adequate traction and counter traction for various operations, including visualization, retraction, dissection, and suturing, with independently controllable manipulators. The merits and demerits of these designs are discussed to provide a reference for developing new surgical robotic systems (SRSs) capable of overcoming the limitations of existing systems and addressing challenges imposed by TORS procedures.

Bio-inspired design translates the knowledge of natural or biological structures or behaviors into novel theories and technologies, providing new directions for research and developments. Although the medical needles for percutaneous intervention technology appear to be mature, biomimetic solutions become popular to further facilitate the performance of the medical needles. In this paper, we review the current state of bio-inspired medical needle designs for percutaneous interventions, including a variety of biomimetic mechanisms and insertion strategies. Existing and experimental designs of biomimetic medical needles are classified into five groups with respect to the applications, while their characteristics are identified and discussed. Such classification and discussion will not only provide technical insights into previous studies but also identify undiscovered directions for future research.

Background and aimMagnifying image-enhanced endoscopy was demonstrated to have higher diagnostic accuracy than white-light endoscopy. However, differentiating early gastric cancers (EGCs) from benign lesions is difficult for beginners. We aimed to determine whether the computer-aided model for the diagnosis of gastric lesions can be applied to videos rather than still images.MethodsA total of 719 magnifying optical enhancement images of EGCs, 1,490 optical enhancement images of the benign gastric lesions, and 1,514 images of background mucosa were retrospectively collected to train and develop a computer-aided diagnostic model. Subsequently, 101 video segments and 671 independent images were used for validation, and error frames were labeled to retrain the model. Finally, a total of 117 unaltered full-length videos were utilized to test the model and compared with those diagnostic results made by independent endoscopists.ResultsExcept for atrophy combined with intestinal metaplasia (IM) and low-grade neoplasia, the diagnostic accuracy was 0.90 (85/94). The sensitivity, specificity, PLR, NLR, and overall accuracy of the model to distinguish EGC from non-cancerous lesions were 0.91 (48/53), 0.78 (50/64), 4.14, 0.12, and 0.84 (98/117), respectively. No significant difference was observed in the overall diagnostic accuracy between the computer-aided model and experts. A good level of kappa values was found between the model and experts, which meant that the kappa value was 0.63.ConclusionsThe performance of the computer-aided model for the diagnosis of EGC is comparable to that of experts. Magnifying the optical enhancement model alone may not be able to deal with all lesions in the stomach, especially when near the focus on severe atrophy with IM. These results warrant further validation in prospective studies with more patients. A ClinicalTrials.gov registration was obtained (identifier number: NCT04563416).Clinical Trial RegistrationClinicalTrials.gov, identifier NCT04563416.

Computational simulations can accelerate the design and modelling of origami robots and mechanisms. This paper presents a computational method using algorithms developed in Python to generate different tessellated origami crease patterns simultaneously. This paper aims to automate this process by introducing a system that automatically generates origami crease patterns in Scalable Vector Graphics format. By introducing different parameters, variations of the same underlying tessellated crease pattern can be obtained. The user interface consists of an input file where the user can input the desired parameters, which are then processed by an algorithm written in Python to generate the respective origami 2D crease patterns. These origami crease patterns can serve as inputs to current origami design software and algorithms to generate origami design models for faster and easier visual comparison. This paper utilizes a basic biomimetic inspiration origami pattern to demonstrate the functionality by varying underlying crease pattern parameters that give rise to symmetric and asymmetric spring origami 3D structures. Furthermore, this paper conducts a qualitative analysis of the origami design outputs of an origami simulator from the input crease patterns and the respective manual folding of the origami structure.

Survival analysis is a critical task in glioma patient management due to the inter and intra tumor heterogeneity. In clinical practice, clinicians estimate the survival with their experience, which can be biased and optimistic. Over the past decades, diverse survival analysis approaches were proposed incorporating distinct data such as imaging and genetic information. The remarkable advancements in imaging and high throughput omics and sequencing technologies have enabled the acquisition of this information of glioma patients efficiently, providing novel insights for survival estimation in the present day. Besides, in the past years, machine learning techniques and deep learning have emerged into the field of survival analysis of glioma patients trading off the traditional statistical analysis-based survival analysis approaches. In this survey paper, we explore the prognostic parameters acquired, utilizing diagnostic imaging techniques and genomic platforms for survival or risk estimation of glioma patients. Further, we review the techniques, learning and statistical analysis algorithms, along with their benefits and limitations used for prognosis prediction. Consequently, we highlight the challenges of the existing state-of-the-art survival prediction studies and propose future directions in the field of research.

A high-accuracy unsupervised classification model is developed in a multimode self-interference microring resonator (SIMRR). For the SIMRR, there are many whispering gallery modes (WGMs) present. Each of these resonance modes supported by the SIMRR has a different response to different target parameters, so that the SIMRR-based sensor has the super capability to distinguish between multiple components. In the classification model, principal component analysis (PCA) is firstly used to reduce the dimensionality of this multimode sensing information from the SIMRR-based sensor. When the original higher-dimensional data points are projected onto the lower-dimensional data with only the first few principal components, they can be easily categorized into several different types by using density-based spatial clustering of application with noise (DBSCAN) algorithm. As an example, the unsupervised classification method is numerically validated based on a designed three-gas SIMRR-based sensor. The numerical results prove that the classification model can achieve an ultra high classification accuracy for the designed three-gas sensor with more than 60 dB in signal-to-noise ratio.

BackgroundDuring COVID-19, clinical and health care demands have been on the rapid rise. Major challenges that have arisen during the pandemic have included a lack of testing kits, shortages of ventilators to treat severe cases of COVID-19, and insufficient accessibility to personal protective equipment for both hospitals and the public. New technologies have been developed by scientists, researchers, and companies in response to these demands. ObjectiveThe primary objective of this review is to compare different supporting technologies in the subjugation of the COVID-19 spread. MethodsIn this paper, 150 news articles and scientific reports on COVID-19–related innovations during 2020-2021 were checked, screened, and shortlisted to yield a total of 23 articles for review. The keywords “COVID-19 technology,” “COVID-19 invention,” and “COVID-19 equipment” were used in a Google search to generate related news articles and scientific reports. The search was performed on February 1, 2021. These were then categorized into three sections, which are personal protective equipment (PPE), testing methods, and medical treatments. Each study was analyzed for its engineering characteristics and potential social impact on the COVID-19 pandemic. ResultsA total of 9 articles were selected for review concerning PPE. In general, the design and fabrication of PPE were moving toward the direction of additive manufacturing and intelligent information feedback while being eco-friendly. Moreover, 8 articles were selected for reviewing testing methods within the two main categories of molecular and antigen tests. All the inventions endeavored to increase sensitivity while reducing the turnaround time. However, the inventions reported in this review paper were not sufficiently tested for their safety and efficiency. Most of the inventions are temporary solutions intended to be used only during shortages of medical resources. Finally, 6 articles were selected for the review of COVID-19 medical treatment. The major challenge identified was the uncertainty in applying novel ideas to speed up the production of ventilators. ConclusionsThe technologies developed during the COVID-19 pandemic were considered for review. In order to better respond to future pandemics, national reserves of critical medical supplies should be increased to improve preparation. This pandemic has also highlighted the need for the automation and optimization of medical manufacturing.

Reported wearable dry electrodes have limited long-term use due to their imperfect skin compliance and high motion artifacts. Here, the authors report an intrinsically conductive, stretchable polymer dry electrode with excellent self-adhesiveness for long-term high-quality biopotential detection.

Objective: To test the feasibility of a real time miniature endoscope system for imaging the nasopharynx. Study design: Preclinical assessment on skull model and cadaver. Methods: A 3.5 mm miniature endoscope was fabricated and the image capture of the nasopharynx was investigated by positioning the miniature camera system at the posterior free edge of the vomer bone. Wireless real time transmission of the images and quality was tested in a skull model. Next, three nasopharyngeal surveillance miniature camera system were developed for possible clinical translation. Two prototypes were anchored on the nasal septum and the last prototype was designed using a patient self-administered surveillance process. These prototypes were tested for feasibility on both the phantom skull and cadaveric model. Risk assessments were also performed to assess risk, safety and validate the reliability of the material utilized for clinical translation. Results: Insertion and anchorage of the miniature surveillance endoscope prototypes at the vomer bone were feasible on all 3 prototypes. The quality of captured images was reasonable and miniaturized camera was responsive to pan at different angles so that the entire nasopharynx may be surveyed. Risk assessments on the material such as pull out test, breaking force analysis, finite element test and tensile strength test were reliable for possible clinical translation. Conclusions: Real time miniature endoscope system for surveillance of nasopharyngeal cancer is feasible. Clinical translation of this technology was possible but requires further refinement in enhancing image quality and wireless transmission of the captured images.

This paper presents an Unscented Kalman Filter (UKF)-based method to achieve high-precision motion estimation of cable-driven forceps for a robot-assisted surgical system. We analyze the operational/working principle of revolute joints of a 3-degree-of-freedom (3-DOF) cable-driven surgical manipulator. Then a gripper jaw is selected as a representative joint, which is actuated by a single-motor cable-driven mechanism with a reset spring. The corresponding system dynamics comprehend the mass, elasticity, damping, and friction of steel cables. By using the displacement and velocity of reset cable and the rotation angle of motor as observations, the motion estimation model based on UKF is derived. The estimation accuracy is verified experimentally, with the errors of absolute and root-mean-square (RMS) of less than 0.5 deg and 0.2 deg respectively. By comparisons with the least square methods (LSMs), the installation strategy of only one displacement sensor on the reset cable is determined, which is conducive to further refinements of the mechanism. Furthermore, the external force loading experiments are performed, with the RMS estimation error of less than 0.5 deg for the external force of no more than 250 g applied on the tip of the gripper jaw. These experimental results validate the motion estimation accuracy of cable-driven forceps, without requiring sensors on the end joints or slender tool shaft of surgical instruments.

Designing artificial sensory neural system for neuroprosthetics and smart robotics applications remains a challenge. Here, the authors demonstrate an all-in-one bionic sensory transmission nerve capable integrating the functions of perception, recognition and transmission of mechano-sensitive signal.

Although ultrasound (US) scan or diagnosis became widely employed in the 20th century, it still plays a crucial part in modern medical diagnostics, serving as a diagnostic tool or a therapy process guide. This review provides information on current wearable technologies and applications used in external ultrasound scanning. It offers thorough explanations that could help build upon any project utilizing wearable external US devices. It touches on several aspects of US scanning and reviews basic medical procedure concepts. The paper starts with a detailed overview of ultrasound principles, including the propagation speed of sound waves, sound wave interactions, image resolution, transducers, and probe positioning. After that, it explores wearable external US mounts and wearable external US transducers applied for sonograph purposes. The subsequent section tackles artificial intelligence methods in wearable US scanners. Finally, future external US scan directions are reported, focusing on hardware and software.

To aid physicians in the precision diagnosis of ailments in the cranial region, we propose an overhead collapsible origami-based mount (Over-COM) with the advantages of being mountable, compact, lightweight, portable, and easy-to-use. The Over-COM can hold small diagnosis apparatuses, attach to regions of interest (ROIs) on the head, and adjust the posture and penetration angle of the sensor to detect the optimal medical signal. The prototype of the Over-COM consists of a setup (housing, eight linear actuators, and an IMU) that can be attached to the head with adhesive or straps, and a small box (containing the microcontroller and battery pack) that can be placed away from the patient. In order to verify the performance of the system, experiments investigating the device’s DOFs and scan protocols were carried out. The experimental results demonstrated that the Over-COM could hold the diagnosis device, locate the ROIs, and determine the best sensor posture and penetration angles.

Soft robotic and medical devices will greatly benefit from stretchable and compliant pressure sensors that can detect deformation and contact forces for control and task safety. In addition to traditional 2D buckling via planar substrates, 3D buckling via curved substrates has emerged as an alternative approach to generate tunable and highly convoluted hierarchical wrinkle morphologies. Such wrinkles may provide advantages in pressure sensing, such as increased sensitivity, ultra-stretchability, and detecting changing curvatures. In this work, we fabricated stretchable sensors using wrinkled MXene electrodes obtained from 3D buckling. We then characterized the sensors’ performance in detecting strain, pressure, and vibrations. The fabricated wrinkled MXene electrode exhibited high stretchability of up to 250% and has a strain sensitivity of 0.1 between 0 and 80%. The fabricated bilayer MXene pressure sensor exhibited a pressure sensitivity of 0.935 kPa−1 and 0.188 kPa−1 at the lower (

As one of the minimally invasive surgeries (MIS), transoral robotic surgery (TORS) contributes to excellent oncological and functional outcomes. This paper introduces a compliant and flexible robotic system for transoral surgery, consisting of an execution part with flexible parallel mechanisms and a positioning part with a continuum structure. A pilot cadaveric study that mimics the procedure of the TORS using an intact cadaveric human head was conducted to evaluate the feasibility and efficiency of this robotic system. Both the initial setup time and the time cost by the robot to safely access the deep surgical area in the upper aerodigestive tract are shortened due to the enlarged workspace, compact structure, and increased flexibility. The proposed surgical robotic system is preliminarily demonstrated to be feasible for TORS, especially for the in-depth surgical sites in the upper aerodigestive tract.

There is compelling support for widening the role of computed tomography (CT) for COVID-19 in clinical and research scenarios. Reverse transcription polymerase chain reaction (RT-PCR) testing, the gold standard for COVID-19 diagnosis, has two potential weaknesses: the delay in obtaining results and the possibility of RT-PCR test kits running out when demand spikes or being unavailable altogether. This perspective article discusses the potential use of CT in conjunction with RT-PCR in hospitals lacking sufficient access to RT-PCR test kits. The precedent for this approach is discussed based on the use of CT for COVID-19 diagnosis and screening in the United Kingdom and China. The hurdles and challenges are presented, which need addressing prior to realization of the potential roles for CT artificial intelligence (AI). The potential roles include a more accurate clinical classification, characterization for research roles and mechanisms, and informing clinical trial response criteria as a surrogate for clinical outcomes.

A novel carrier phase recovery algorithm is proposed for coherent optical systems with circular multilevel quadrature amplitude modulation (C-mQAM). After amplitude segmentation and phase rotation, the particular distribution of the constellation points in a C-mQAM signal is exploited to construct a special cost function to provide a rough estimate of phase noise. The cost function can be replaced with a simple cosine function, and only two or three test phases are required for the calculation of its parameters. The performances of different cost functions are compared and simulation results show that the cost function can be chosen with the high phase noise tolerance and low computational complexity. Maximum-likelihood phase noise estimation algorithm is combined with the proposed algorithm to mitigate residual phase noise. Compared to the single-stage blind phase search and n-phase-shift keying partitioning algorithms, the numerical results demonstrate that the proposed two-stage algorithm shares similar phase noise tolerance and offers a lower computational complexity for a 28-GBaud back-to-back coherent optical QAM transmission system.

Minimally invasive procedures have gained ever-increasing popularity due to their advantages of smaller incisions, faster recoveries, fewer complications, and reduced scarring to name a few. With the force exertion and curvilinear flexibility at their distal end effectors, the continuum tubular robots have the potential to perform robot-assisted trans-orifice minimally invasive surgery, such as transnasal and transoral operations. During these procedures, it is important and challenging for the continuum tubular robot to automatically adjust its pose according to the target surgical sites and compensate for undesired disturbance, such as respiratory motions. In this paper, a singularity-avoidance visual servoing algorithm based on Jacobian Optimization has been proposed to improve safety and control continuum tubular robots based on intra-operative visual feedback in confined environments. Without the prior knowledge of robot kinematics or hand-eye calibration between the robot and the endoscope, the proposed model-free eye-in-hand visual servoing technique is capable of accomplishing the targeting tasks by adopting the safety-enhanced singularity avoidance mechanism and an efficient image-processing algorithm. The multiple experiments, including simulations, experiments conducted in a confined environment, and cadaveric studies, have been implemented and demonstrated to illustrate the superiority of the proposed singularity-avoidance visual servoing method.

Intensity modulation/direct detection (IM/DD) orthogonal frequency division multiplexing (OFDM) is very suitable for high-speed cost-sensitive passive optical network (PON) applications. However, real-time OFDM systems are sensitive to synchronization bias, and thus symbol timing synchronization (STS) becomes a critical issue. We proposed a proportional-sign cross-correlation (PS-CC) STS algorithm with the advantages of distance-independence and low resource utilization. In the proposed PS-CC STS algorithm, the sign operation is applied instead of the multiplication operation with high computational complexity to decrease the resource utilization and the characteristic of low resource utilization will drive its application in real-time systems. Meanwhile, we use field programmable gate array (FPGA) to design a baseband IM/DD OFDM receiver with pipeline structure and built a universal loop test system, which is applied to implement the proposed PS-CC STS algorithm and evaluate its performance. In the experiment of a 16-QAM OFDM-PON system, a 30-km fiber transmission only results in 1.98% ripple on the peak amplitude of correlation, which verifies the distance-independence of the proposed method.

With the emerging need for human–machine interactions, multi-modal sensory interaction is gradually pursued rather than satisfying common perception forms (visual or auditory), so developing flexible, adaptive, and stiffness-variable force-sensing devices is the key to further promoting human–machine fusion. However, current sensor sensitivity is fixed and nonadjustable after fabrication, limiting further development. To solve this problem, we propose an origami-inspired structure to achieve multiple degrees of freedom (DoFs) motions with variable stiffness for force-sensing, which combines the ductility and flexibility of origami structures. In combination with the pneumatic actuation, the structure can achieve and adapt the compression, pitch, roll, diagonal, and array motions (five motion modes), which significantly increase the force adaptability and sensing diversity. To achieve closed-loop control and avoid excessive gas injection, the ultra-flexible microfiber sensor is designed and seamlessly embedded with an approximately linear sensitivity of ∼0.35 Ω/kPa at a relative pressure of 0–100 kPa, and an exponential sensitivity at a relative pressure of 100–350 kPa, which can render this device capable of working under various conditions. The final calibration experiment demonstrates that the pre-pressure value can affect the sensor’s sensitivity. With the increasing pre-pressure of 65–95 kPa, the average sensitivity curve shifts rightwards around 9 N intervals, which highly increases the force-sensing capability towards the range of 0–2 N. When the pre-pressure is at the relatively extreme air pressure of 100 kPa, the force sensitivity value is around 11.6 Ω/N. Therefore, our proposed design (which has a low fabrication cost, high integration level, and a suitable sensing range) shows great potential for applications in flexible force-sensing development.

There are high risks of infection for surgeons during the face-to-face COVID-19 swab sampling due to the novel coronavirus’s infectivity. To address this issue, we propose a flexible transoral robot with a teleoperated configuration for swab sampling. The robot comprises a flexible manipulator, an endoscope with a monitor, and a master device. A 3-prismatic-universal (3-PU) flexible parallel mechanism with 3 degrees of freedom (DOF) is used to realize the manipulator’s movements. The flexibility of the manipulator improves the safety of testees. Besides, the master device is similar to the manipulator in structure. It is easy to use for operators. Under the guidance of the vision from the endoscope, the surgeon can operate the master device to control the swab’s motion attached to the manipulator for sampling. In this paper, the robotic system, the workspace, and the operation procedure are described in detail. The tongue depressor, which is used to prevent the tongue’s interference during the sampling, is also tested. The accuracy of the manipulator under visual guidance is validated intuitively. Finally, the experiment on a human phantom is conducted to demonstrate the feasibility of the robot preliminarily.

Swabbing tests have proved to be an effective method of diagnosis for a wide range of diseases. Potential occupational health hazards and reliance on healthcare workers during traditional swabbing procedures can be mitigated by self-administered swabs. Hence, we report possible methods to apply closed kinematic chain theory to develop a self-administered viral swab to collect respiratory specimens. The proposed sensorized swab models utilizing hollow polypropylene tubes possess mechanical compliance, simple construction, and inexpensive components. In detail, the adaptation of the slider-crank mechanism combined with concepts of a deployable telescopic tubular mechanical system is explored through four different oral swab designs. A closed kinematic chain on suitable material to create a developable surface allows the translation of simple two-dimensional motion into more complex multi-dimensional motion. These foldable telescopic straws with multiple kirigami cuts minimize components involved in the system as the characteristics are built directly into the material. Further, it offers a possibility to include soft stretchable sensors for realtime performance monitoring. A variety of features were constructed and tested using the concepts above, including 1) tongue depressor and cough/gag reflex deflector; 2) changing the position and orientation of the oral swab when sample collection is in the process; 3) protective cover for the swabbing bud; 4) a combination of the features mentioned above.

Surgical scene understanding is a key barrier for situation-aware robotic surgeries and the associated surgical training. With the presence of domain shifts and the inclusion of new instruments and tissues, learning domain generalization (DG) plays a pivotal role in expanding instrument–tissue interaction detection to new domains in robotic surgery. Mimicking the ability of humans to incrementally learn new skills without forgetting their old skills in a similar domain, we employ incremental DG on scene graphs to predict instrument–tissue interaction during robot-assisted surgery. To achieve incremental DG, incorporate incremental learning (IL) to accommodate new instruments and knowledge-distillation-based student–teacher learning to tackle domain shifts in the new domain. Additionally, we designed an enhanced curriculum by smoothing (E-CBS) based on Laplacian of Gaussian (LoG) and Gaussian kernels, and integrated it with the feature extraction network (FEN) and graph network to improve the instrument–tissue interaction performance. Furthermore, the FEN’s and graph network’s logits are normalized by temperature normalization (T-Norm), and its effect in model calibration was studied. Quantitative and qualitative analysis proved that our incrementally-domain generalized interaction detection model was able to adapt to the target domain (transoral robotic surgery) while retaining its performance in the source domain (nephrectomy surgery). Additionally, the graph model enhanced by E-CBS and T-Norm outperformed other state-of-the-art models, and the incremental DG technique performed better than the naive domain adaption and DG technique.

Deployable mechanism has received more attention in the medical field due to its simple structure, dexterity, and flexibility. Meanwhile, the advantages of the Magnetic Anchoring and Guidance System (MAGS) are further highlighted by the fact that the operators can remotely control the corresponding active and passive magnetic parts in vivo. Additionally, MAGS allows the untethered manipulation of intracorporeal devices. However, the conventional instruments in MAGS are normally rigid, compact, and less flexible. Therefore, to solve this problem, four novel deployable tubular mechanisms, Design 1 (Omega-shape mechanism), Design 2 (Fulcrum-shape mechanism), Design 3 (Archway-shape mechanism), and Design 4 (Scissor-shape mechanism) in this paper, are proposed integrated with MAGS to realize the laser steering capability. Firstly, this paper introduces the motion mechanism of the four designs and analyzes the motion characterization of each structure through simulation studies. Further, the prototypes of four designs are fabricated using tubular structures with embedded magnets. The actuation success rate, the workspace characterization, the force generation and the load capability of four mechanisms are tested and analyzed based on experiments. Then, the demonstration of direct laser steering via macro setup shows that the four mechanisms can realize the laser steering capability within the error of 0.6 cm. Finally, the feasibility of indirect laser steering via a macro-mini setup is proven. Therefore, such exploration demonstrates that the application of the deployable tubular mechanisms integrated with MAGS towards in vivo treatment is promising.

COVID-19 can induce severe respiratory problems that need prolonged mechanical ventilation in the intensive care unit. While Open Tracheostomy (OT) is the preferred technique due to the excellent visualization of the surgical field and structures, Percutaneous Tracheostomy (PT) has proven to be a feasible minimally invasive alternative. However, PT's limitation relates to the inability to precisely enter the cervical trachea at the exact spot since the puncture is often performed based on crude estimation from anatomical laryngeal surface landmarks. Besides, there is no absolute control of the trajectory and force required to make the percutaneous puncture into the trachea, resulting in inadvertent injury to the cricoid ring, cervical esophagus, and vessels in the neck. Therefore, we hypothesize that a flexible mini-robotic system, incorporating the robotic needling technology, can overcome these challenges by allowing the trans-oral robotic instrument of the cervical trachea. This approach promises to improve current PT technology by making the initial trachea puncture from an “inside-out” approach, rather than an “outside-in” manner, fraught with several technical uncertainties.

A lack of sensory feedback often hinders minimally invasive operations. Although endoscopy has addressed this limitation to an extent, endovascular procedures such as angioplasty or stenting still face significant challenges. Sensors that rely on a clear line of sight cannot be used because it is unable to gather feedback in blood environments. During the stent deployment procedure, feedback on the deployed stent's state is critical because a partially open stent can affect the blood flow. Despite this, no robust and noninvasive clinical solutions that allow real‐time monitoring of the stent deployment exists. In recent years, radio frequency (RF)‐based sensors can detect the shape and material of an object that is hidden from the direct line of sight. Herein, the use of a 3D RF‐based imaging sensor and a novel Convolutional Neural Network (CNN) called StentNet is proposed for detecting the stent's state without a need for a clear line of sight. The StentNet achieves an overall accuracy of 90% in detecting the state of an occluded stent in the test dataset. Compared with an existing CNN model, the StentNet significantly outperforms the 3D LeNet in the evaluation metrics such as accuracy, precision, recall, and F1‐score.

We propose a consensus control strategy for multiple unmanned underwater vehicles (multi-UUVs) with unmeasurable disturbances under the fixed and switching topologies. The current methods presented in the literature mainly solve tracking consensus problems with the disturbances under the time-invariant and time-varying topologies, respectively. In the paper, considering the complex nonlinear and couple model of the UUV, the technique of the feedback linearization is employed to transform the nonlinear UUV model into a second-order integral UUV model. For unmeasurable disturbances consisting of unknown model uncertainties and external disturbance for each UUV, we design the distributed extended state observer (DESO) to estimate the disturbances using the UUV position information relative to its neighbours. Moreover, leader-following multi-UUVs consensus control algorithm that enables all following UUVs to track the leader UUV state information based on the estimation state information from the DESO is proposed for two types of topologies, the fixed and switching topologies. Finally, simulation results are shown to demonstrate the effectiveness of the algorithm proposed in the paper.

Digital holography assisted with inline phase-shifting methods has the benefit of a large field of view and a high resolution, but it is limited in dynamic imaging due to sequential detection of multiple holograms. Here we propose and experimentally demonstrate a single-shot phase-shifting digital holography system based on a highly stable on-axis Fizeau-type polarization interferometry. The compact on-axis design of the system with the capability of instantaneous recording of multiple phase-shifted holograms and with robust stability features makes the technique a novel tool for the imaging of complex-valued dynamic objects. The efficacy of the approach is demonstrated experimentally by complex field imaging of various kinds of reflecting-type static and dynamic objects. Moreover, a quantitative analysis on the robust phase stability and sensitivity of the technique is evaluated by comparing the approach with conventional phase-shifting methods. The high phase stability and dynamic imaging potential of the technique are expected to make the system an ideal tool for quantitative phase imaging and real-time imaging of dynamic samples.

Ionic pressure sensors are made of ionic compounds suspended in a suitable solvent mixture. When external pressure is exerted on them, it is reflected as a change in electrical parameters due to physical deformation and a redistribution of ions within the sensing medium. Variations in the composition and material of the sensing medium result in different pressure sensors with varying operating ranges and sensitivity. This work presents the design and fabrication procedure of a novel soft-pressure sensor for a very low-pressure range (7.498×10−4 Ω/mmHg) was observed when using 40% glycerin in the sensing medium, filled in a toroidal geometry with outer and inner channel diameters of 8 mm and 7 mm, respectively. The proposed sensor is entirely soft and can be designed to conform to any desired geometry.

Background/Aims: Peri-operative cerebral ischemia reperfusion injury is one of the most serious peri-operative complications that can be aggravated in patients with diabetes. A previous study showed that microglia NOX2 (a NADPH oxidase enzyme) may play an important role in this process. Here, we investigated whether increased microglial derived gp91phox, also known as NOX2, reduced oxygen glucose deprivation (OGD) after induction of hyperglycemia (HG). Methods: A rat neuronal-microglial in vitro co-culture model was used to determine the effects of gp91phox knockdown on OGD after HG using six treatment groups: A rat microglia and neuron co-culture model was established and divided into the following six groups: high glucose + scrambled siRNA transfection (HG, n = 5); HG + gp91phoxsiRNA transfection (HG-gp91siRNA, n = 5); oxygen glucose deprivation + scrambled siRNA transfection (OGD, n = 5); OGD + gp91phoxsiRNA transfection (OGD-gp91siRNA, n = 5); HG + OGD + scrambled siRNA transfection (HG-OGD, n = 5); and HG + OGD + gp91phoxsiRNA transfection (HG-OGD-gp91siRNA, n = 5). The neuronal survival rate was measured by the MTT assay, while western blotting was used to determine gp91phox expression. Microglial derived ROS and neuronal apoptosis rates were analyzed by flow cytometry. Finally, the secretion of cytokines, including IL-6, IL-8, TNF-α, and 8-iso-PGF2α was determined using an ELISA kit. Results: Neuronal survival rates were significantly decreased by HG and OGD, while knockdown of gp91phox reversed these rates. ROS production and cytokine secretion were also significantly increased by HG and OGD but were significantly inhibited by knockdown of gp91phoxsiRNA. Conclusion: Knockdown of gp91phoxsiRNA significantly reduced oxidative stress and the inflammatory response, and alleviated neuronal damage after HG and OGD treatment in a rat neuronal-microglial co-culture model.

The fear of needles and pain prevents some patients from seeking intravitreal treatment, which drives our group to develop a needleless device for performing intravitreal injections. A prototype for an electro-magnetically actuated needleless injector, based on Halbach arrays, is described and characterized in a laboratory setting. The implication of the prototype for needleless ocular drug delivery is investigated. This investigation is intended to improve drug delivery of glaucoma medication with a safe needleless approach. We detail the design aspects of the injector and characterized the device with custom-made phantoms. It was observed that, despite delivering the drug bolus to the center, the viscous vitreous phantom indicated vorticities similar to counter rotating vortex pairs, which could cause damage to the retina. The observed peak velocity during the phantom experiments was 6.1 mm/sec at the retinal layer, indicating that the delivery bolus can impart shear forces to the retina via the vitreous.

With the challenging noisy measurements, the maneuvering safety and comfort level of hovercraft navigation can be significantly increased by accurate motion parameter estimation. Because traditional hard/soft thresholding schemes have discontinuities and deviation shortcomings, an improved wavelet thresholding method is proposed to smooth and estimate the dynamic motion parameters. Then, an interscale correlation method is introduced to improve the accuracy of judgment of the wavelet coefficients near the threshold. The newly improved wavelet thresholding and inter-scale correlation scheme can increase the adaptability of the estimator function and improve the accuracy of judgment of wavelet coefficients. Afterwards, a series of numerical simulation experiments are carried out by using four benchmark signals with three different noise levels. Compared with traditional hard/soft thresholding and semi-soft thresholding methods, the proposed improved parameter estimation scheme has a great advantage in denoising the signal noise and reducing the peak interference and the error between decomposition signal and the original signal. Finally, the proposed improved parameter estimation scheme was applied to a certain hovercraft in sea trial. Representatively, some important safety and comfort indicator parameters are selected from actual hovercraft motion measurements to verify the effect of the proposed scheme. From the data analysis, it is shown that the improved scheme behaves an outstanding performance in denoising and estimating for practical application, which improves the safety and comfort of navigation. Otherwise, the effective estimation of indicator parameters will make the further active control be available to assure maneuvering safety and comfort level of hovercraft navigation.

Soft robotics is a research field growing rapidly with primary focuses on the prototype design, development of soft robots and their applications. Due to their highly deformable features, it is difficult to model and control such robots in a very precise way compared with the conventional rigid structured robots. Hence, the calibration and parameter identification problems of an underactuated robotic hand with soft fingers are important, but have not been investigated intensively. In this paper, we present a comparative study on the calibration of a soft robotic hand. The calibration problem is framed as an AX = YB problem with the partially known matrix A. The identifiability of the parameters is analyzed, and calibration methods based on nonlinear optimization (i.e., Levenberg-Marquardt method and interior-point method) and evolutionary computation (i.e., differential evolution) are presented. Extensive simulation tests are performed to examine the parameter identification using the three methods in a comparative way. The experiments are conducted on the real soft robotic-hand setup. The fitting, interpolating, and extrapolating errors are presented as well.

In this paper, a practical adaptive online constructive fuzzy control (AOCFC) algorithm is proposed to handle the trajectory tracking problem for the unmanned surface vessel under unknown time-varying uncertainties. In the AOCFC algorithm, the dynamic surface control technology combined with “logical virtual vessel”can program the rational reference route while avoiding the problem of “complexity explosion.”Besides, the proposed online constructive fuzzy approximator (OCFA) is devised to deal with the unknown time-varying uncertainties. The OCFA has two advantages: first, it can estimate the uncertainties without exact information of the dynamic model and external environmental disturbances; second, it employs decoupled distance measure and structure learning mechanism to dynamically and parsimoniously self-constructing fuzzy rules. At the same time, we have proved that the tracking errors of the closed-loop control system are uniformly ultimately bounded. Finally, the simulation result and comprehensive comparison demonstrate the proposed controller's performance and effectiveness.

The steady rise of deployable structures and mechanisms based on kirigami and origami principles has brought about design innovations that yield flexible and lightweight robots. These robots are designed based on desirable locomotion mechanisms and often incorporate additional materials to support their flexible structure to enable load-bearing applications and considerable efficient movement. One tetherless way to actuate these robots is via the use of magnets. This paper incorporates magnetic actuation and kirigami structures based on the lamina emergent mechanism (LEM). Three designs of magnetic-actuated LEMs (triangular prism, single LEM (SLEM), alternating mirror dual LEM (AMDLEM)) are proposed, and small permanent magnets are attached to the structures’ flaps or legs that rotate in response to an Actuating Permanent Magnet (APM) to yield stick-slip locomotion, enabling the robots to waddle and crawl on a frictional surface. For preliminary characterization, we actuate the three designs at a frequency of 0.6 Hz. We observed the triangular prism, SLEM, and AMDLEM prototypes to achieve horizontal speeds of 4.3 mm/s, 10.7 mm/s, and 12.5 mm/s on flat surfaces, respectively. We further explore how changing different parameters (actuation frequency, friction, leg length, stiffness, compressibility) affects the locomotion of the different mechanisms.

Nowadays, origami folding in combination with actuation mechanisms can offer deployable structure design, yield compliance, and have several properties of soft material. An easy complex folding pattern can yield an array of functionalities in actuated hinges or active spring elements. This paper presents various cylinder origami robot designs that can be untethered magnetically actuated. The different designs are analyzed and compared to achieve the following three types of motion: Peristaltic, rolling, and turning in different environments, namely, board, sandpaper, and sand. The proposed origami robot is able translate 53 mm in peristaltic motion within 20 s and is able to roll one complete cycle in 1 s and can turn ≈180∘ in 1.5 s. The robot also demonstrated a peristaltic locomotion at a speed of ≈2.5 mm s−1, ≈1.9 mm s−1, and ≈1.3 mm s−1 in board, sandpaper, and sand respectively; rolling motion at a speed of 1 cycle s−1, ≈0.66 cycles s−1, and ≈0.33 cycles s−1 in board, sandpaper, and sand respectively; and turning motion of ≈180∘, ≈83∘, and ≈58∘ in board, sandpaper, and sand respectively. The evaluation of the robotic motion and actuation is discussed in detail in this paper.

Actuators with variable stiffness have vast potential in the field of compliant robotics. Morphological shape changes in the actuators are possible, while they retain their structural strength. They can shift between a rigid load-carrying state and a soft flexible state in a short transition period. This work presents a hydraulically actuated soft actuator fabricated by a fully 3D printing of shape memory polymer (SMP). The actuator shows a stiffness of 519 mN/mm at 20 ∘C and 45 mN/mm at 50 ∘C at the same pressure (0.2 MPa). This actuator demonstrates a high stiffness variation of 474 mN/mm (10 times the baseline stiffness) for a temperature change of 30 ∘C and a large variation (≈1150%) in average stiffness. A combined variation of both temperature (20–50 ∘C) and pressure (0–0.2 MPa) displays a stiffness variation of 501 mN/mm. The pressure variation (0–0.2 MPa) in the actuator also shows a large variation in the output force (1.46 N) at 50 ∘C compared to the output force variation (0.16 N) at 20 ∘C. The pressure variation is further utilized for bending the actuator. Varying the pressure (0–0.2 MPa) at 20 ∘C displayed no bending in the actuator. In contrast, the same variation of pressure at 50 ∘C displayed a bending angle of 80∘. A combined variation of both temperature (20–50 ∘C) and pressure (0–0.2 MPa) shows the ability to bend 80∘. At the same time, an additional weight (300 g) suspended to the actuator could increase its bending capability to 160∘. We demonstrated a soft robotic gripper varying its stiffness to carry various objects.

Valves are largely useful for treatment assistance devices, e.g., supporting fluid circulation movement in the human body. However, the valves presently used in biomedical applications still use materials that are rigid, non-compliant, and hard to integrate with human tissues. Here, we propose biologically-inspired, stimuli-responsive valves and evaluate N-Isopropylacrylamide hydrogels-based valve (NPHV) and PAAm-alginate hydrogels-based valve (PAHV) performances with different chemical syntheses for optimizing better valve action. Once heated at 40 ∘C, the NPHV outperforms the PAHV in annular actuation (NPHV: 1.93 mm displacement in 4 min; PAHV: 0.8 mm displacement in 30 min). In contrast, the PAHV exhibits a flow rate change of up to 20%, and a payload of 100% when the object is at 100 ∘C. The PAHV demonstrated a completely soft, stretchable circular gripper with a high load-to-weight ratio for diversified applications. These valves are fabricated with a simple one-pot method that, once further optimized, can offer transdisciplinary applications.

Stretchable, skin-interfaced, and wearable strain sensors have risen in recent years due to their wide-ranging potential applications in health-monitoring devices, human motion detection, and soft robots. High aspect ratio (AR) silver nanowires (AgNWs) have shown great potential in the flexible and stretchable strain sensors due to the high conductivity and flexibility of AgNW conductive networks. Hence, this work aims to fabricate highly stretchable, sensitive, and linear kirigami strain sensors with high AR AgNWs. The AgNW synthesis parameters and process windows have been identified by Taguchi’s design of experiment and analysis. Long AgNWs with a high AR of 1556 have been grown at optimized synthesis parameters using the one-pot modified polyol method. Kirigami sensors were fabricated via full encapsulation of AgNWs with Ecoflex silicon rubber. Kirigami-patterned strain sensors with long AgNWs show high stretchability, moderate sensitivity, excellent linearity (R2 = 0.99) up to 70% strain and can promptly detect finger movement without obvious hysteresis.

Image-based surgical instrument tracking in robot-assisted surgery is an active and challenging research area. Having a real-time knowledge of surgical instrument location is an essential part of a computer-assisted intervention system. Tracking can be used as visual feedback for servo control of a surgical robot or transformed as haptic feedback for surgeon–robot interaction. In this Letter, the authors apply a multi-domain convolutional neural network for fast 2D surgical instrument tracking considering the application for multiple surgical tools and use a focal loss to decrease the effect of easy negative examples. They further introduce a new dataset based on m2cai16-tool and their cadaver experiments due to the lack of established public surgical tool tracking dataset despite significant progress in this field. Their method is evaluated on the introduced dataset and outperforms the state-of-the-art real-time trackers.

Flexible and stretchable tactile sensors that are printable, nonplanar, and dynamically morphing are emerging to enable proprioceptive interactions with the unstructured surrounding environment. Owing to its varied range of applications in the field of wearable electronics, soft robotics, human-machine interaction, and biomedical devices, it is required of these sensors to be flexible and stretchable conforming to the arbitrary surfaces of their stiff counterparts. The challenges in maintaining the fundamental features of these sensors, such as flexibility, sensitivity, repeatability, linearity, and durability, are tackled by the progress in the fabrication techniques and customization of the material properties. This review is aimed at summarizing the recent progress of rapid prototyping of sensors, printable material preparation, required printing properties, flexible and stretchable mechanisms, and promising applications and highlights challenges and opportunities in this research paradigm.

Intra-abdominal pressure (IAP) is closely correlated with intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) diagnoses, indicating the need for continuous monitoring. Early intervention for IAH and ACS has been proven to reduce the rate of morbidity. However, the current IAP monitoring method is a tedious process with a long calibration time for a single time point measurement. Thus, there is the need for an efficient and continuous way of measuring IAP. Herein, a stretchable capacitive pressure sensor with controlled microstructures embedded into a cylindrical elastomeric mold, fabricated as a pressure sensing sleeve, is presented. The sensing sleeve can be readily deployed onto intrabody catheter balloons for pressure measurement at the site. The thin and highly conformable nature of the pressure sensing sleeve captures the pressure change without hindering the functionality of the foley catheter balloon.