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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]

Objective: We present a general framework of simultaneous needle shape reconstruction and control input generation for robot-assisted spinal injection procedures, without continuous imaging feedback., Methods: System input-output mapping is generated with a real-time needle-tissue interaction simulation, and single-core FBG sensor readings are used as local needle shape feedback within the same simulation framework. FBG wavelength shifts due to temperature variation is removed by exploiting redundancy in fiber arrangement., Results: Targeting experiments performed on both plastisol lumbar phantoms as well as an ex vivo porcine lumbar section achieved in-plane tip errors of 0.6 ± 0.3 mm and 1.6 ± 0.9 mm , and total tip errors of 0.9 ± 0.7 mm and 2.1 ± 0.8 mm for the two testing environments., Significance: Our clinically inspired control strategy and workflow is self-contained and not dependent on the modality of imaging guidance. The generalizability of the proposed approach can be applied to other needle-based interventions where medical imaging cannot be reliably utilized as part of a closed-loop control system for needle guidance.

Background: Master-slave remote control technology allows patients to be treated promptly during transport and also reduces the risk of contagious infections. Endotracheal intubation, guided by endoscopy and a master-slave system, enables doctors to perform the procedure efficiently and accurately., Methods: In this paper, we present the development of a master-slave controlled endotracheal intubation robot (EIR). It is based on operation incremental mapping, a weighted recursive average filtering method to reduce vibration, and a virtual fixture designed to reduce mishandling in minimally invasive surgery., Results: Simulation analysis of the master-slave control demonstrates that the weighted recursive average filtering method effectively reduces vibration, while the virtual fixture assists in confining the operator's movement within a delimited area. Experimental validation confirms the validity of the robot's structural design and control method., Conclusions: The developed robot successfully achieves the necessary motion for endotracheal intubation surgery through master-slave control., (© 2024 John Wiley & Sons Ltd.)

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]