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The paper studies the influence of human factor and clinical constraints specific to mechanical devices for medical purpose. environment (with a limited workspace, inside or outside the patient body). A medical robot is usually a complex system including mechanical structure, human-machine interface (HMI), electronic components, and software controller. All these components are integrated to perform various tasks for daily medical applications. Because any failure may become very critical, medical robots must function safely and with high reliability, so that designing medical robots for safe human interaction can be considered a real challenge. In order to respect the clinical constrains, a safety real-time controller has been designed. [ABSTRACT FROM AUTHOR]

This article explores the challenges of continuum and magnetic soft robotics for medical applications, extending from model development to an interdisciplinary perspective. First, we established a unified model framework based on algebra and geometry. The research progress and challenges in principle models, data-driven, and hybrid modeling were then analyzed in depth. Simultaneously, a numerical analysis framework for the principle model was constructed. Furthermore, we expanded the model framework to encompass interdisciplinary research and conducted a comprehensive analysis, including an in-depth case study. Current challenges and the need to address meta-problems were identified through discussion. Overall, this review provides a novel perspective on understanding the challenges and complexities of continuum and magnetic soft robotics in medical applications, paving the way for interdisciplinary researchers to assimilate knowledge in this domain rapidly. [ABSTRACT FROM AUTHOR]

This paper offers a comprehensive examination of the development and implementation of advanced safety protocols in the Patient Positioning System (PPS) for radiosurgery. In an era where precision and safety are increasingly crucial in medical procedures, particularly radiosurgery, the implementation of sophisticated safety measures in PPS is vital. This research delves into the detailed design of the system, emphasizing the sensor and controller mechanisms employed. A significant focus is placed on comparing single-loop and dual-loop control systems, assessing their impact on the precision, accuracy, and repeatability of the PPS. The study showcases how dual-loop control demonstrates superior performance in these areas, leading to enhanced patient safety and treatment outcomes. Additionally, the paper discusses the integration of these safety protocols within the system's architecture, underscoring the practical implications of these advanced measures in augmenting patient safety and treatment effectiveness. [ABSTRACT FROM AUTHOR]

Soft surgical robots represent a groundbreaking innovation in the field of medical technology. These robots utilize soft, deformable materials to navigate and interact with delicate structures inside the human body, such as organs and blood vessels, with enhanced safety. They have the potential to transform healthcare by expanding the capabilities of minimally invasive surgeries, targeted drug delivery, and precise diagnostics. They can also reduce patient discomfort, recovery times, and the risk of complications, infections, and accidental injuries. The key to the functionality of soft surgical robots lies in their actuation mechanisms. Various actuation methods have been developed, including pneumatic, magnetic, tendon-driven, smart materials (like shape memory alloys, dielectric elastomer actuators, and ionic polymer–metal composites), and hybrid combinations of these mechanisms. Each actuator type offers unique advantages and challenges, making the selection of the right actuation solution a complex task. This review paper aims to provide a comprehensive understanding of these soft actuation mechanisms and their applications in surgical robotics. It delves into the current state of the art in various applications, from endoscopes and catheters to cardiac support devices, bioinspired inchworm robots, and more. While significant progress has been made in the field of soft actuators for surgical robotics, this paper identifies several challenges that must still be overcome to effectively apply these innovations in real-life surgical procedures on human patients. [ABSTRACT FROM AUTHOR]

Taking advantage of individualization, automation and intelligentization in care, medical robots has potential in the smart healthcare under artificial intelligence in medicine. This paper summarized the research status of medical robots, and analyzed its application and potential problems in care of patients with Parkinson's disease, in order to provided reference for the development of smart healthcare under the background of “China Brain Project” and China's aging population. (医疗机器人有着个性化、自动化和智能化等照护优势, 在医学人工智能的智慧照护领域有着广大的应用前景。本文梳理了医疗机器人的研究现状, 并对其在帕金森患者照护领域的应用及存在问题进行分析, 旨在为“中国脑计划”与中国老龄化背景下的智慧照护提供借鉴与启发。)

In the clinical treatment of Alzheimer's disease, one of the most important tasks is evaluating its severity for diagnosis and therapy. However, traditional testing methods are deficient, such as their susceptibility to subjective factors, incomplete evaluation, low accuracy, or insufficient granularity, resulting in unreliable evaluation scores. To address these issues, we propose an objective dementia severity scale based on MRI (ODSS-MRI) using contrastive learning to automatically evaluate the neurological function of patients. The approach utilizes a deep learning framework and a contrastive learning strategy to mine relevant information from structural magnetic resonance images to obtain the patient's neurological function level score. Given that the model is driven by the patient's whole brain imaging data, but without any possible biased manual intervention or instruction from the physician or patient, it provides a comprehensive and objective evaluation of the patient's neurological function. We conducted experiments on the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset, and the results showed that the proposed ODSS-MRI was correlated with the stages of AD 88.55% better than all existing methods. This demonstrates its efficacy to describe the neurological function changes of patients during AD progression. It also outperformed traditional psychiatric rating scales in discriminating different stages of AD, which is indicative of its superiority for neurological function evaluation. [ABSTRACT FROM AUTHOR]

This article explores the challenges of continuum and magnetic soft robotics for medical applications, extending from model development to an interdisciplinary perspective. First, we established a unified model framework based on algebra and geometry. The research progress and challenges in principle models, data-driven, and hybrid modeling were then analyzed in depth. Simultaneously, a numerical analysis framework for the principle model was constructed. Furthermore, we expanded the model framework to encompass interdisciplinary research and conducted a comprehensive analysis, including an in-depth case study. Current challenges and the need to address meta-problems were identified through discussion. Overall, this review provides a novel perspective on understanding the challenges and complexities of continuum and magnetic soft robotics in medical applications, paving the way for interdisciplinary researchers to assimilate knowledge in this domain rapidly.

This paper offers a comprehensive examination of the development and implementation of advanced safety protocols in the Patient Positioning System (PPS) for radiosurgery. In an era where precision and safety are increasingly crucial in medical procedures, particularly radiosurgery, the implementation of sophisticated safety measures in PPS is vital. This research delves into the detailed design of the system, emphasizing the sensor and controller mechanisms employed. A significant focus is placed on comparing single-loop and dual-loop control systems, assessing their impact on the precision, accuracy, and repeatability of the PPS. The study showcases how dual-loop control demonstrates superior performance in these areas, leading to enhanced patient safety and treatment outcomes. Additionally, the paper discusses the integration of these safety protocols within the system’s architecture, underscoring the practical implications of these advanced measures in augmenting patient safety and treatment effectiveness.

Inspired by insects in nature, an increasing number of soft robots have been proposed to mimic their locomotion patterns. As a wireless actuation method, the magnetic actuation technique has been widely applied to drive soft magnetic robots for diverse applications. Although recent works on soft materials have stimulated the development of soft robots, it is challenging to achieve the efficient movement of soft robots for in vivo biomedical application. Inspired by centipede locomotion, a soft octopodal robot is designed in this paper. The robot is fabricated by mixing magnetic particles with silicone polymers, which is then magnetized by a specific magnetic field. The prototypes can be actuated by an external magnetic field (5–8 mT) produced by custom-made electromagnetic coils. Experimental results show that the soft robot can move at a high speed in the range of 0.536–1.604 mm/s on different surfaces, including paper, wood, and PMMA. This indicates that the soft robot can achieve comparable speeds to other robots, while being driven by a lower magnitude, resulting in energy savings. Furthermore, it achieves a high speed of 0.823 mm/s on the surface of a pig colon. The fine capabilities of the soft robot in terms of crossing uneven biological surfaces and carrying external loads are demonstrated. The results indicate that the reported soft robot exhibits promising applications in the biomedical field. [ABSTRACT FROM AUTHOR]

The magnetic field has unique advantages in manipulating miniature robots working inside the human body, such as high transparency to biological tissue and good controllability for field generation. Generally, the actuated magnetic robot can be classified into two categories: tethered devices like intravascular microcatheters and untethered devices like helical swimmers. Among these, the tethered devices have a long history and good clinical application prospects, considering their high‐dose delivery and easy removal after the procedure. As an evolution of traditional continuum medical devices, the integration with magnetic actuation provides them with better scalability and improved dexterity. Although rapidly developed in the last two decades, the field of tethered magnetic robots requires further advancements in terms of design, fabrication, modeling, and control, especially for clinical applications. Herein, the recent progress of magnetically actuated continuum medical robots is focused on, intending to offer readers a comprehensive survey of the state‐of‐the‐art technologies and an information collection for future system design. [ABSTRACT FROM AUTHOR]

In view of the problem that the current research rarely pays attention to the planning of actual rehabilitation actions, a trajectory planning strategy of the lower limb rehabilitation actions for cable-driven rehabilitation robots (CDRRs) is presented in this paper. First, the inverse kinematics model and forward kinematics model of the patient's lower limb meeting the needs of rehabilitation training were established. Then, a direct solution method based on space geometry was proposed according to the state and constraints of the patient. The mapping from the patient's lower limb end point trajectory to the patient's lower leg trajectory was realized by the above two ways. Finally, considering of the movement of the winders, the inverse kinematics model of the reconfigurable CDRR was derived. Through a reasonable cable distribution, patient's lower leg was regarded as the mobile platform of the CDRR, and the mapping between the ankle joint trajectory of the patient's lower limb and the cable length change of the CDRR was finally realized. Taking flexion knee joint rehabilitation action as an example, it is shown that this trajectory planning strategy can plan the trajectory of the required rehabilitation action in a three-dimensional space in the simulation and experimental results. [ABSTRACT FROM AUTHOR]

Purpose: Conventional robotic ultrasound systems were utilized with patients in supine positions. Meanwhile, the limitation of the systems is that it is difficult to evacuate the patients in case of emergency (e.g., patient discomfort and system failure) because the patients are restricted between the robot system and bed. Therefore, we validated a feasibility study of seated-style echocardiography using a robot. Method: Preliminary experiments were conducted to verify the following two points: (1) diagnostic image quality due to the sitting posture angle and (2) physical load due to the sitting posture angle. For reducing the physical burden, two unique mechanisms were incorporated into the system: (1) a leg pendulum base mechanism to reduce the load on the legs when the lateral bending angle increases, and (2) a roll angle division by a lumbar lateral bending and thoracic rotation mechanisms. Results: Preliminary results demonstrated that adjusting the diagnostic posture angle allowed to obtain the views, including cardiac disease features, as in the conventional examination. The results also demonstrated that the body load reduction mechanism incorporated in the results could reduce the physical load in the seated echocardiography. Furthermore, this system was shown to provide greater safety and shorter evacuation times than conventional systems. Conclusion: These results indicate that diagnostic echocardiographic images can be obtained by seated-style echocardiography. It was also suggested that the proposed system can reduce the physical load and guarantee a sense of safety and emergency evacuation. These results demonstrated the possibility of the usage of the seated-style echocardiography robot. [ABSTRACT FROM AUTHOR]

Human–computer interaction (HCI) is deployed in various real-time applications, including healthcare, for automated patient response. In such applications, robot-assisted interactive scenarios are modeled to handle patient queries and provide precise information. Timely query sensing and accurate data analysis are required to achieve accurate patient responses. In this study, responsive policy decision (RPD) using manifold mediator learning (MML) is introduced to improve data detection accuracy and accuracy in robot-assisted HCI applications. The initial decision-making process in data analytics is based on interaction stages and medical data detection. After identifying the most appropriate policy, respondents are provided with time-based responses based on the patient's queries. When it comes to improving the accuracy of data analysis decisions, machine learning uses policies based on interaction stages and previous state efficiency of HCI responses. The experimental analysis proves the reliability of the proposed method by improving the accuracy of data analysis and reducing its complexity and response time for the varying queries and time intervals. [ABSTRACT FROM AUTHOR]

The magnetic field has unique advantages in manipulating miniature robots working inside the human body, such as high transparency to biological tissue and good controllability for field generation. Generally, the actuated magnetic robot can be classified into two categories: tethered devices like intravascular microcatheters and untethered devices like helical swimmers. Among these, the tethered devices have a long history and good clinical application prospects, considering their high‐dose delivery and easy removal after the procedure. As an evolution of traditional continuum medical devices, the integration with magnetic actuation provides them with better scalability and improved dexterity. Although rapidly developed in the last two decades, the field of tethered magnetic robots requires further advancements in terms of design, fabrication, modeling, and control, especially for clinical applications. Herein, the recent progress of magnetically actuated continuum medical robots is focused on, intending to offer readers a comprehensive survey of the state‐of‐the‐art technologies and an information collection for future system design.

Nowadays robotic technology provides massive advantages over traditional procedures, including shorter hospitalization and rehabilitation time, and less pain and discomfort. This paper presents the fundamental requirements of a surgical robot, its applications, advantages and disadvantages of different topologies and concludes with a comparison between surgical robots and surgeons.

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An important issue in medical robotics is communication between physicians and robots. Speech-based communication is of particular advantage in robot-assisted surgery. It frees the surgeon's hands; hence, he can focus on the principal tasks. Man-machine voice communication is the subject of research in various domains (industry, social robotics), but medical robots are very specific. They must precisely synchronize their activities with operators. Voice commands must be possibly short. They must be executed without significant delays. An important factor is the use of a vision system that provides visual information in direct synchronization with surgeon actions. Its functions could be also controlled using speech. The aim of the research presented in this paper was to develop a method facilitating creation of voice-controlled medical robotic systems, fulfilling the mentioned requirements and taking into account possible scenarios of man-machine collaboration in such systems. A robot skill description (RSD) format was proposed in order to facilitate programming of voice control applications. A sample application was developed, and experiments were conducted in order to draw conclusions regarding the usefulness of speech-based interfaces in medical robotics. The results show that a reasonable selection of system functions controlled by voice may lead to significant improvement of man-machine collaboration. [ABSTRACT FROM AUTHOR]

Medical robots with audio-video-haptic streams, as indispensable devices for remote healthcare, are playing ever-increasing roles in mitigating the spread of infectious diseases. However, existing medical robots are far from precise and efficient because of the following two technical challenges, including i) how to ensure the haptic fidelity for precise manipulation, and ii) how to alleviate the impact of haptic streams on the quality of visual navigation for efficient operation. To this end, this work explores the benefits of edge-based cross-modal communications (CMCs), which take full advantage of potential correlations among different modalities’ streams, to realize high reliability and throughput. Specifically, to compensate for the reliability loss caused by wireless transmission, a semantic-aided cross-modal reconstruction framework is firstly designed at edge nodes for high haptic fidelity. Then, a user experience-driven stream scheduling strategy is developed to enhance the visual quality by fully leveraging edge computing and network slicing. In particular, different from traditionally interrupting audio/video stream transmission to prioritize haptic streams, we jointly schedule resources to different modalities’ streams via estimating haptic arrival time. Finally, as a classical case study, we independently construct a remote throat swab sampling platform based on CMCs to evaluate practical performance, and numerical results indicate the significant improvements in terms of various metrics. [ABSTRACT FROM AUTHOR]

In the clinical treatment of Alzheimer’s disease, one of the most important tasks is evaluating its severity for diagnosis and therapy. However, traditional testing methods are deficient, such as their susceptibility to subjective factors, incomplete evaluation, low accuracy, or insufficient granularity, resulting in unreliable evaluation scores. To address these issues, we propose an objective dementia severity scale based on MRI (ODSS-MRI) using contrastive learning to automatically evaluate the neurological function of patients. The approach utilizes a deep learning framework and a contrastive learning strategy to mine relevant information from structural magnetic resonance images to obtain the patient’s neurological function level score. Given that the model is driven by the patient’s whole brain imaging data, but without any possible biased manual intervention or instruction from the physician or patient, it provides a comprehensive and objective evaluation of the patient’s neurological function. We conducted experiments on the Alzheimer’s disease Neuroimaging Initiative (ADNI) dataset, and the results showed that the proposed ODSS-MRI was correlated with the stages of AD 88.55% better than all existing methods. This demonstrates its efficacy to describe the neurological function changes of patients during AD progression. It also outperformed traditional psychiatric rating scales in discriminating different stages of AD, which is indicative of its superiority for neurological function evaluation.

Achieving high repetitive accuracy and operation uniformity of small lesion targeting are the main challenges in robot-assisted procedures of MRI-guided breast biopsy. In this paper, we present a visual servo controlled robotic system for MRI-guided breast intervention. This robot system is developed based on the manual control version of previous publication. Zhang et al. (2019). The robot system exploits a cable-driven series-parallel mechanism and pneumatic controlled acupuncture mechanism, robot motion is guided by a machine vision system. The kinematic model of the robot is established, a control method of combining forward kinematics and visual servo control of a series-parallel robot is proposed to fulfil accurate control of the needle. A robot motion compensation method based on vision is developed, and the accuracy of the lesion targeting of the robot system is improved by establishing a feedback control mechanism. Repetitive accuracy results shows that the average error of targeting different lesions is between 1.29 mm to 2.42 mm, compared to previous manual control method, the visual control can provide significant improved accuracy. Comprehensive image quality test including signal-to-noise ratio (SNR) test, distortion test and uniformity test are carried out. The SNR variation is less than 10%, distortion is less than 1%, and uniformity is larger than 96%. Comparative experiments are conducted to verify the system’s visual servo control accuracy, MR image quality is evaluated to verify MRI compatibility under working condition. The experimental results show the robot satisfies the operational requirements and can provide effective assistance in clinical breast biopsy. [ABSTRACT FROM AUTHOR]

Inspired by insects in nature, an increasing number of soft robots have been proposed to mimic their locomotion patterns. As a wireless actuation method, the magnetic actuation technique has been widely applied to drive soft magnetic robots for diverse applications. Although recent works on soft materials have stimulated the development of soft robots, it is challenging to achieve the efficient movement of soft robots for in vivo biomedical application. Inspired by centipede locomotion, a soft octopodal robot is designed in this paper. The robot is fabricated by mixing magnetic particles with silicone polymers, which is then magnetized by a specific magnetic field. The prototypes can be actuated by an external magnetic field (5–8 mT) produced by custom-made electromagnetic coils. Experimental results show that the soft robot can move at a high speed in the range of 0.536–1.604 mm/s on different surfaces, including paper, wood, and PMMA. This indicates that the soft robot can achieve comparable speeds to other robots, while being driven by a lower magnitude, resulting in energy savings. Furthermore, it achieves a high speed of 0.823 mm/s on the surface of a pig colon. The fine capabilities of the soft robot in terms of crossing uneven biological surfaces and carrying external loads are demonstrated. The results indicate that the reported soft robot exhibits promising applications in the biomedical field.

Interventional robotic systems have been deployed with all existing imaging modalities in an expansive portfolio of therapies and surgeries. Over the years, literature reviews have painted a comprehensive portrait of the translation of the underlying technology from research to practice. While many of these robots performed promisingly in preclinical settings, only a handful of them managed to evolve further, break through the commercialization boundary, and even fewer reached a wide-scale adoption. Despite the undeniable success of service robotics in general and particularly in some sophisticated medical applications, image-guided robotics’ impact remained modest compared to other surgical areas, especially laparoscopic minimally invasive surgery. This article aims to embrace the state of the art on the one hand, provide a comprehensive narrative of the situation described, support future system developers, and facilitate the translation from scientific research to applied clinical technology development. [ABSTRACT FROM AUTHOR]

Continuum robots are not constructed with discrete joints but, instead, change shape and position their tip by flexing along their entire length. Their narrow curvilinear shape makes them well suited to passing through body lumens, natural orifices, or small surgical incisions to perform minimally invasive procedures. Modeling and controlling these robots are, however, substantially more complex than traditional robots comprised of rigid links connected by discrete joints. Furthermore, there are many approaches to achieving robot flexure. Each presents its own design and modeling challenges, and to date, each has been pursued largely independently of the others. This article attempts to provide a unified summary of the state of the art of continuum robot architectures with respect to design for specific clinical applications. It also describes a unifying framework for modeling and controlling these systems while additionally explaining the elements unique to each architecture. The major research accomplishments are described for each topic and directions for the future progress needed to achieve widespread clinical use are identified. [ABSTRACT FROM AUTHOR]

Nowadays robotic technology provides massive advantages over traditional procedures, including shorter hospitalization and rehabilitation time, and less pain and discomfort. This paper presents the fundamental requirements of a surgical robot, its applications, advantages and disadvantages of different topologies and concludes with a comparison between surgical robots and surgeons. [ABSTRACT FROM AUTHOR]

Straight-line needle insertion is a prevalent tool in surgical interventions in the brain, such as Deep Brain Stimulation and Convection-Enhanced Delivery, that treat a range of conditions from Alzheimer's disease to brain cancer. Using a steerable needle to execute curved trajectories and correct positional deviation could enable more intervention possibilities, while reducing the risk of complication in these procedures. This paper experimentally identifies model parameters using an expectation-maximization (EM) algorithm for two different steerable needle models. The results compared a physically motivated model to the established bicycle needle model and found the former to be preferred for modeling soft brain tissue needle insertion. The results also supported the experimentally parameterized models' use in future applications such as needle steering control. [ABSTRACT FROM AUTHOR]

Recent research points to the fact that new medical technological innovations are just as relevant in the context of long‐term care or chronic care as they are in the context of acute care. In the spirit of the Nuffield Foundation recommendations, this paper explores the possibilities of using robotic aides in long‐term care and identifies the tensions that must be considered and addressed if robotics is to be introduced successfully in nursing homes. Our examination is two‐pronged. First, we delve into a fundamental issue surrounding AI, namely that of consciousness. We argue that automation will always have only a limited use in caregiving since caregiving as an activity requires the use of human‐type, that is, organic, consciousness. We support the thesis that the emergence and formation of human‐type consciousness require feelings such as empathy and the sense of touch, which, in turn, create the sense of kinship with fellow human beings. And second, we examine the benefits as well as risks of using robotic aides such as ZORA and PARO in long‐term care facilities. More specifically, we look at ZORA's use in a group setting, and PARO's use in an individual setting. We emphasize that long‐term care is one‐on‐one care, including but not limited to intimate care. Crucially, we argue that touch is at the heart of this type of care. We argue that some of the tensions with the use of robotic aides are generated precisely because of the lack of human touch. [ABSTRACT FROM AUTHOR]

Medical ultrasound (US) systems are widely used for the diagnosis of internal tissues. However, there are challenges associated with acquiring and interpreting US images, such as incorrect US probe placement and limited available spatial information. In this study, we expand the capabilities of medical US imaging using a robotic framework with a high level of autonomy. A 3D camera is used to capture the surface of an anthropomorphic phantom as a point cloud, which is then used for path planning and navigation of the US probe. Robotic positioning of the probe is realised using an impedance controller, which maintains stable contact with the surface during US scanning and compensates for uneven and moving surfaces. Robotic US positioning accuracy is measured to be 1.19± 0.76mm. The mean force along US probe ${z}$ –direction is measured to be 6.11±1.18N on static surfaces and 6.63±2.18N on moving surfaces. Overall lowest measured force of 1.58N demonstrates constant probe-to-surface contact during scanning. Acquired US images are used for the 3D reconstruction and multi-modal visualization of the surface and the inner anatomical structures of the phantom. Finally, K-means clustering is used to segment different tissues. Best segmentation accuracy of the jugular vein according to Jaccard similarity coefficient is measured to be 0.89. With such an accuracy, this system could substantially improve autonomous US acquisition and enhance the diagnostic confidence of clinicians.

A robotic surgical system capable of performing minimally invasive surgery (MIS) is proposed in this paper. Based on the requirements of MIS, a compliant, seven- degrees of freedom (7-DOF) pneumatically actuated mechanism is designed. A remote center of motion (RCM) as a parallelogram mechanism for holding the laparoscopic camera is also developed. The operating workspace of robotic surgical system is determined considering the physical constraints imposed by mechanical joints. The simulation results show that the robotic system meets the design requirement. This research will lay a good foundation for the development of a compliant surgical robot to assist in MIS.

This paper presents a multi-purpose gripping and incision tool-set to reduce the number of required manipulators for targeted therapeutics delivery in Minimally Invasive Surgery. We have recently proposed the use of multi-arm Concentric Tube Robots (CTR) consisting of an incision, a camera, and a gripper manipulator for deep orbital interventions, with a focus on Optic Nerve Sheath Fenestration (ONSF). The proposed prototype in this research, called Gripe-Needle, is a needle equipped with a sticky suction cup gripper capable of performing both gripping of target tissue and incision tasks in the optic nerve area by exploiting the multi-tube arrangement of a CTR for actuation of the different tool-set units. As a result, there will be no need for an independent gripper arm for an incision task. The CTR innermost tube is equipped with a needle, providing the pathway for drug delivery, and the immediate outer tube is attached to the suction cup, providing the suction pathway. Based on experiments on various materials, we observed that adding a sticky surface with bio-inspired grooves to a normal suction cup gripper has many advantages such as, 1) enhanced adhesion through material stickiness and by air-tightening the contact surface, 2) maintained adhesion despite internal pressure variations, e.g. due to the needle motion, and 3) sliding resistance. Simple Finite Element and theoretical modeling frameworks are proposed, based on which a miniature tool-set is designed to achieve the required gripping forces during ONSF. The final designs were successfully tested for accessing the optic nerve of a realistic eye phantom in a skull eye orbit, robust gripping and incision on units of a plastic bubble wrap sample, and manipulating different tissue types of porcine eye samples.

An important issue in medical robotics is communication between physicians and robots. Speech-based communication is of particular advantage in robot-assisted surgery. It frees the surgeon’s hands; hence, he can focus on the principal tasks. Man-machine voice communication is the subject of research in various domains (industry, social robotics), but medical robots are very specific. They must precisely synchronize their activities with operators. Voice commands must be possibly short. They must be executed without significant delays. An important factor is the use of a vision system that provides visual information in direct synchronization with surgeon actions. Its functions could be also controlled using speech. The aim of the research presented in this paper was to develop a method facilitating creation of voice-controlled medical robotic systems, fulfilling the mentioned requirements and taking into account possible scenarios of man-machine collaboration in such systems. A robot skill description (RSD) format was proposed in order to facilitate programming of voice control applications. A sample application was developed, and experiments were conducted in order to draw conclusions regarding the usefulness of speech-based interfaces in medical robotics. The results show that a reasonable selection of system functions controlled by voice may lead to significant improvement of man-machine collaboration.

Minimally invasive surgery is of high interest for interventional medicine since the smaller incisions can lead to less pain and faster recovery for patients. The current standard-of-care involves a range of affordable, manual, hand-held rigid tools, whose limited dexterity and range of adoptable shapes can prevent access to confined spaces. In contrast, recently developed roboticized tools that can provide increased accessibility and dexterity to navigate and perform complex tasks often come at the cost of larger, heavier, and grounded devices that are teleoperated, posing a new set of challenges. In this article, we propose a new hand-held concentric tube robot with an associated position control method that has the dexterity and precision of large roboticized devices, while maintaining the footprint of a traditional hand-held tool. The device shows human-in-the-loop control performance that meets the requirements of the targeted application, percutaneous abscess drainage. In addition, a small user study illustrates the advantage of combining rigid body motion of the device with more precise motions of the tip, thus showing the potential to bridge the gap between traditional hand-held tools and grounded robotic devices. [ABSTRACT FROM AUTHOR]

Abstract Magnetic resonance imaging (MRI) scanners do not provide only high‐resolution medical imaging but also magnetic robot actuation and tracking. However, the rotational motion capabilities of MRI‐powered wireless magnetic capsule‐type robots have been limited due to the very high axial magnetic field inside the MRI scanner. Medical functionalities of such robots also remain a challenge due to the miniature robot designs. Therefore, a wireless capsule‐type reversible orientation‐locking robot (REVOLBOT) is proposed that has decoupled translational motion and planar orientation change capability by locking and unlocking the rotation of a spherical ferrous bead inside the robot on demand. Such an on‐demand locking/unlocking mechanism is achieved by a phase‐changing wax material in which the ferrous bead is embedded inside. Controlled and on‐demand hyperthermia and drug delivery using wireless power transfer‐based Joule heating induced by external alternating magnetic fields are the additional features of this robot. The experimental feasibility of the REVOLBOT prototype with steerable navigation, medical function, and MRI tracking capabilities with an 1.33 Hz scan rate is demonstrated inside a preclinical 7T small‐animal MRI scanner. The proposed robot has the potential for future clinical use in teleoperated minimally invasive treatment procedures with hyperthermia and drug delivery capabilities while being wirelessly powered and monitored inside MRI scanners.

Magnetic resonance imaging (MRI) scanners do not provide only high‐resolution medical imaging but also magnetic robot actuation and tracking. However, the rotational motion capabilities of MRI‐powered wireless magnetic capsule‐type robots have been limited due to the very high axial magnetic field inside the MRI scanner. Medical functionalities of such robots also remain a challenge due to the miniature robot designs. Therefore, a wireless capsule‐type reversible orientation‐locking robot (REVOLBOT) is proposed that has decoupled translational motion and planar orientation change capability by locking and unlocking the rotation of a spherical ferrous bead inside the robot on demand. Such an on‐demand locking/unlocking mechanism is achieved by a phase‐changing wax material in which the ferrous bead is embedded inside. Controlled and on‐demand hyperthermia and drug delivery using wireless power transfer‐based Joule heating induced by external alternating magnetic fields are the additional features of this robot. The experimental feasibility of the REVOLBOT prototype with steerable navigation, medical function, and MRI tracking capabilities with an 1.33 Hz scan rate is demonstrated inside a preclinical 7T small‐animal MRI scanner. The proposed robot has the potential for future clinical use in teleoperated minimally invasive treatment procedures with hyperthermia and drug delivery capabilities while being wirelessly powered and monitored inside MRI scanners. [ABSTRACT FROM AUTHOR]

Manual catheter‐based interventions (CBIs) suffer from exposure of the interventionalists to X‐ray, and dependence of their performance on the expertise and fatigue level of the interventionalists. Robot‐assisted catheterization systems (RACS) have been introduced in recent years to improve the efficiency of CBIs; however, using them is still associated with some difficulties such as set‐up dependency to a specific type of intervention instrument, not being portable, and offering limited options of operation modes. The objective of this research is to develop a new RACS to address these shortcomings. We propose Althea II as an improvement for our previously introduced RACS, Althea I. Althea II is designed for both research purposes and clinical applications including catheter‐based cardiovascular interventions. Althea II benefits from a novel structural design leading to a significantly reduced weight and making the device inclusive for a broader range of intervention instruments. Also, a tip detection algorithm is developed and integrated into the graphical user interface (GUI) to enable image‐based navigation, and accordingly, fully automatic navigation. Althea II has improved the outcome of catheter‐based interventions by increased accuracy and precision of the intervention. The system can navigate the catheter tip to a designated target with an accuracy higher than 90% in both velocity and positioning mode. The device is associated with an upgraded GUI equipped with a strong tip detection algorithm with an accuracy of 0.05 mm. Moreover, Althea II gains from a quicker assembly time (20 minutes, which equals five times faster). The independency from specific catheters, several modes of function, an imaged‐based feedback control, portability, and a remote function should allow operation even from beginners and reduce X‐ray exposure. The preliminary research studies verified the accuracy and repeatability of Althea II, demonstrated the feasibility and applicability of using the set‐up in multiple applications, and highlighted the improved set‐up capabilities over the currently available RACS. [ABSTRACT FROM AUTHOR]

In this article, a magnetic actuation system based on three mobile electromagnetic coils is designed and a control strategy for the system is proposed. Enhanced flexibility combined with optimization algorithms enables the system to satisfy various requirements in applications, such as avoiding collision between the coils and the obstructions within the workspace, placing the coils to optimal positions to enhance energy efficiency, generating wide varieties of magnetic field for complex tasks, and tracking the location of the robot with enlarged workspace. To reach that purpose, a model of the system is built for magnetic field calculation, and a real-time optimization algorithm based on particle swarm optimization combined with a collision detection algorithm is proposed and implemented to calculate optimal positions for coils and at the same time avoid collision. We fabricate a prototype system, named RoboMag, to prove the concept. Simulations and experiments on helical swimmer and soft robot are conducted to evaluate the performance. Compared with two conventional control strategies, the demanded currents for long-distance actuation are reduced by up to 62.7%. The calculation process is conducted in real time and the coils are able to avoid collision with the barriers inside the workspace during actuation. Moreover, generation and steering of a microrobotic swarm is demonstrated, showing the capability of the system in generating programmed dynamic fields for complicated tasks. [ABSTRACT FROM AUTHOR]

Purpose: The following paper is a "Q&A interview" conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry turned successful business leader, regarding the commercialization and challenges of bringing technological inventions to market while overseeing a company. This paper aims to discuss these issues. Design/methodology/approach: The interviewee is Dr Gary Guthart, Chief Executive Officer (CEO) at Intuitive Surgical, Inc., and a member of the Board of Directors, both roles he has held since 2010. Guthart discusses his journey to becoming the CEO and also shares some of his lessons learned and challenges faced. Findings: Guthart received a bachelor's degree in engineering physics from California, Berkeley. He earned an MS and a PhD in engineering from the California Institute of Technology. Guthart's first scientific experience came early in his career in a Human Factors Lab at NASA, supporting a team studying human performance assessment of pilots. Guthart was then part of the core team developing foundational technology for computer-enhanced surgery at SRI International. While at SRI, he also developed algorithms for vibration and acoustic control of large-scale systems. Guthart joined Intuitive Surgical as part of the first engineering team in 1996 as a Control Systems Analyst. He was promoted to Vice President of Engineering in 2002 and was appointed President and Chief Operating Officer in 2008. Originality/value: Under Dr Gary Guthart's leadership and his more than 25 years of medical technology, engineering, scientific and management experience, Intuitive Surgical, Inc., the world's most successful medical robotics company, has grown to: more than 8,000 employees; nearly 6,000 da Vinci systems sold; more than 8.5 million procedures performed and an increase in stock (NASDAQ: ISRG) of more than 600%. Guthart is also on the Board of Directors for Illumina, Inc., and a member of the Board of Directors for the Silicon Leadership Group. [ABSTRACT FROM AUTHOR]

The continuum manipulators, which have gradually become a research hotspot of minimally invasive surgery have the characteristics of small size, lightweight, and better environmental adaptability. In this paper, a two degrees of freedom continuum manipulator with notches is proposed. The kinematic and mechanical models of the notch continuum manipulator are coupled. The output driving force of the motor is needed to control the manipulator. Due to the drift of the current of the motor, the accuracy of the control is low. In order to solve the above problem, the constant curvature assumption is realized by changing the structural parameters of the notches. The continuum manipulator mechanics model is established through the analysis of the continuum manipulator structure. The calculation of the deformation angle of a single notch of the manipulator is carried out. The overall deformation of the manipulator is derived through iterative algorithms. The stiffness of the continuum manipulator, which can affect the deformation of the continuum manipulator is modified by changing the structural parameters. In this way, the problem of the non-constant curvature deformation under the uniform notch of the continuum manipulator is improved. And the effectiveness of the variable stiffness model is verified by simulation experiments.

The emergence and popularization of medical robots bring great convenience to doctors in treating patients. The core of medical robots is the interaction and cooperation between doctors and robots, so it is crucial to design a simple and stable human-robots interaction system for medical robots. Language is the most convenient way for people to communicate with each other, so in this paper, a DQN agent based on long-short term memory (LSTM) and attention mechanism is proposed to enable the robots to extract executable action sequences from doctors' natural language instructions. For this, our agent should be able to complete two related tasks: 1) extracting action names from instructions. 2) extracting action arguments according to the extracted action names. We evaluate our agent on three datasets composed of texts with an average length of 49.95, 209.34, 417.17 words respectively. The results show that our agent can perform better than similar agents. And our agent has a better ability to handle long texts than previous works. [ABSTRACT FROM AUTHOR]

Robot-assisted surgical procedures have gained much coverage in recent years and favored over manually conducted operations. The medical robots are comprised of manipulators arm that is the multi-degree of freedom positioning devices with a highly non-linear nature to perform various surgical tasks. Due to non-linear effects, robots offer a severe challenge to the control system. Therefore, the control techniques are required for controlling the robots that should be fast enough to accommodate the rapid changes in the system parameters. In this article, the Proportional-Integral-Derivative (PID) controller's performance has been investigated in trajectory control of the Two-Link Robotic Manipulator (TLRM) for reliable functioning of these robots. Tracking error and Control input factors have been used to investigate the PID controller's robustness in trajectory control of 'TLRM.' Euler's-lagrange approach has been used for dynamic analysis of 'TLRM'. This work has been accomplished in the MATLAB®/ Simulink environment. [ABSTRACT FROM AUTHOR]

Straight-line needle insertion is a prevalent tool in surgical interventions in the brain, such as Deep Brain Stimulation and Convection-Enhanced Delivery, that treat a range of conditions from Alzheimer’s disease to brain cancer. Using a steerable needle to execute curved trajectories and correct positional deviation could enable more intervention possibilities, while reducing the risk of complication in these procedures. This paper experimentally identifies model parameters using an expectation-maximization (EM) algorithm for two different steerable needle models. The results compared a physically motivated model to the established bicycle needle model and found the former to be preferred for modeling soft brain tissue needle insertion. The results also supported the experimentally parameterized models’ use in future applications such as needle steering control.

The global shortage of skilled workers and the growing pressure on medical facilities to work profitably and efficiently is increasingly causing clinics and doctors to confront major problems. Especially routine medical interventions should be performed quickly and with few employees. Nevertheless, cost savings must not be at the expense of patients. One way to solve this dilemma is the use of flexible, collaborating robots, so called Cobots, that can be integrated into existing surgical processes. This paper shows the existing requirements for the workplace and the necessary human-machine interface for use in the medical environment. Furthermore, an approach to human-centered workplace design is reported. In addition to the design of the workplace using virtual ergonomics and workplace analyses, the kinematic chain as well as applicable end effectors for medical interventions are presented. In the context of a phantom study the use of the Cobot could be tested and evaluated for the first time. [ABSTRACT FROM AUTHOR]

Rigid robots have taken on a variety of automated manufacturing tasks and have made a huge contribution to industrial development; however, they are not suitable for further wearable applications due to their rigid and bulky structure, poor environmental adaptability, and low safety. Soft robots, which are mainly fabricated with flexible or elastomeric materials, can easily adjust to environmental changes and accomplish complex tasks, offering a new paradigm to achieve human–machine compliance. Soft robots do not replace rigid robots but add diverse features for softer robotic applications. In particular, the use of flexible actuators in robotic systems can realize certain intelligent functions, enrich soft robotic systems and migrate academic research to engineering applications. Currently, the application of flexible actuators in soft robotic fields is still at the embryonic stage. However, tremendous application spaces can be envisaged when combining flexible actuators with soft wearable robotics. Therefore, the current flexible actuators that rely on different external stimuli are addressed herein, and their materials, designs, and approaches suitable for soft robotic applications are highlighted. The application advancement and future perspective of flexible actuator prototypes toward various soft robotics are also discussed.

This paper proposes a new ultrasonography guided arterial puncturing and guidewire insertion mechanism. In conventional arterial puncturing, a physician holds an ultrasound probe in one hand and a needle in the other. Due to the prolong holding of ultrasound probe in hand, physicians and sonographers face musculoskeletal disorders. Also the contact force exerted by the hand of the physician is variable. The purpose of this study is to develop a passive device that will not only hold the ultrasound probe, but also performs needle and guidewire insertion with precision and accuracy. To test the effectiveness of the device, animal experimentation has been performed. This device showed 100% successful insertion rate and the operating time has been reduced from 4.5 minutes to 3.8 minutes. The proposed ultrasound probe holder exerts a stable contact force on the skin of the patient which helps to provide a stable image. [ABSTRACT FROM AUTHOR]