Medical Robotics Research Articles

Measurements Under Biomechanical Stress in Medical Robotics: Diagnosing Pulmonary Impairments by Sensing Breathe Sounds

Measurements Under Biomechanical Stress in Medical Robotics: Diagnosing Pulmonary Impairments by Sensing Breathe Sounds

The LMIT: Light-mediated minimally-invasive theranostics in oncology.

Minimally-invasive diagnosis and therapy have gradually become the trend and research hotspot of current medical applications. The integration of intraoperative diagnosis and treatment is a development important direction for real-time detection, minimally-invasive diagnosis and therapy to reduce mortality and improve the quality of life of patients, so called minimally-invasive theranostics (MIT). Light is an important theranostic tool for the treatment of cancerous tissues. Light-mediated minimally-invasive theranostics (LMIT) is a novel evolutionary technology that integrates diagnosis and therapeutics for the less invasive treatment of diseased tissues. Intelligent theranostics would promote precision surgery based on the optical characterization of cancerous tissues. Furthermore, MIT also requires the assistance of smart medical devices or robots. And, optical multimodality lay a solid foundation for intelligent MIT. In this review, we summarize the important state-of-the-arts of optical MIT or LMIT in oncology. Multimodal optical image-guided intelligent treatment is another focus. Intraoperative imaging and real-time analysis-guided optical treatment are also systemically discussed. Finally, the potential challenges and future perspectives of intelligent optical MIT are discussed.

Wearable flexible pressure sensors: an intriguing design towards microstructural functionalization

Microstructures can endow flexible pressure sensors with high sensitivity and a wide linear sensing range, ensuring the comprehensive sensing performance of medical monitoring and intelligent robots.

An Operating Stiffness Controller for the Medical Continuum Robot Based on Impedance Control.

Continuum manipulators can conform to curvilinear paths and manipulate objects in complex environments, which makes it emerging to be applied in minimally invasive surgery (MIS). However, different and controllable operating stiffness of the continuum manipulator is required during different stages of surgery to achieve safe access or stable and precise operation. This work proposes an operating stiffness controller (OSC) for the typical tendon-driven continuum manipulator based on the variable impedance control method with Lagrangian dynamic modeling. This controller can adjust the operating stiffness by modifying the driving forces along the driving tendons of the continuum manipulator without changing its material or structure. The proposed OSC converts the damping and stiffness matrices of the impedance control into variable parameters. This merit allows it to dynamically adjust the operating stiffness of the continuum manipulator according to the desired constant or time-varying stiffness. Furthermore, the OSC stability can be proven based on a Lyapunov function, and its stiffness control performances have been analyzed and evaluated in both simulations and experiments. The OSC controller generated average relevant error values of 7.82% and 3.09% for the operating stiffness control experiments with constant and time-varying desired stiffness, respectively. These experimental results indicate that the OSC has high accuracy, stability, and strong robustness in the operating stiffness control tasks.

The application of metaverse in healthcare.

While metaverse is widely discussed, comprehension of its intricacies remains limited to a select few. Conceptually akin to a three-dimensional embodiment of the Internet, the metaverse facilitates simultaneous existence in both physical and virtual domains. Fundamentally, it embodies a visually immersive virtual environment, striving for authenticity, where individuals engage in real-world activities such as commerce, gaming, social interaction, and leisure pursuits. The global pandemic has accelerated digital innovations across diverse sectors. Beyond strides in telehealth, payment systems, remote monitoring, and secure data exchange, substantial advancements have been achieved in artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and blockchain technologies. Nevertheless, the metaverse, in its nascent stage, continues to evolve, harboring significant potential for revolutionizing healthcare. Through integration with the Internet of Medical Devices, quantum computing, and robotics, the metaverse stands poised to redefine healthcare systems, offering enhancements in surgical precision and therapeutic modalities, thus promising profound transformations within the industry.

Closed-Loop Magnetic Control of Medical Soft Continuum Robots for Deflection

Closed-Loop Magnetic Control of Medical Soft Continuum Robots for Deflection

Этические проблемы в области ассистивной робототехники для пожилых людей: философские vs эмпирические исследования

Assistive robotics can provide technological support to meet the growing demand for health and social care as people's physical and cognitive functions decline with age. Companion robots can help elderly people with tasks such as mobility, communication and self-care. But do we have the moral right to delegate the duties of medical personnel to robots? Can robots provide the proper quality of medical care? Such reflections on the future of “machine” healthcare raise serious ethical questions in the field of human-robot interaction and determine not only priority developments in the field of social robotics, but also technological culture as a whole. Contemporary research on ethical issues in the field of assistive robotics for elderly people can be distinguished from two directions - traditional philosophical speculation and applied research with an emphasis on the participation of various stakeholders. The article discusses these two directions in detail, as well as criticism of philosophical and theoretical attitudes from the “empiricists”. In particular, they argue that along with ethical analysis, social expertise and philosophical reasoning, new forms of reflection, dialogue and experimentation are needed that will be much closer to innovative practices and contexts of use. The methodological basis of the article is the principles of Technology Assessment (TA), transdisciplinary research strategies such as the RRI approach, as well as Value-Sensitive Design (VSD). The article describes new options for value-based design, such as Integrative social robotics (ISR), Care-Centered Value-Sensitive Design (CCVSD). These approaches are quite promising for solving philosophical and ethical problems in the field of social robotics for caring for the elderly. But more direct and indirect stakeholders need to be involved in the design and development of medical robots. Based on the Stakeholder Tokens method, it is shown how some ethical problems can be solved in a situation of value conflict between autonomy, human dignity and security.

A Novel Fiber Bragg Grating Three-Dimensional Force Sensor for Medical Robotics

A Novel Fiber Bragg Grating Three-Dimensional Force Sensor for Medical Robotics

Soft Medical Robots and Probes: Concise Survey of Current Advances

Soft robotics has emerged as a new branch of robotics gaining huge research interest in recent decades. Owning intrinsic advantages such as compliance and safety, soft robots are closely associated with the medical requirements of medical robots. This review is written to overview advances in the medical applications of soft robots, either for readers primarily familiar with traditional medical systems, or for researchers planning to develop soft robots for medical applications. Recent publications related to soft medical robots were reviewed to represent the state’, ’of’, ’the’, ’art advances in this field. The review tends to compress the scope to trunk’, ’shaped soft robots and appraise the status of soft robots and their distance from clinical use. Several papers related to the construction and capabilities of soft robots were referenced. Roughly 190 related articles published in the current period from 2018 to the publication date (representing almost 90% of the references to the theme totally identified) were reviewed. Structure of soft robots, advances in technology, and the aptitudes in medical applications were discussed. The trunk’, ’like soft robots conspicuously are proposed for applications including robot assisted surgery where a probe is inserted into the human body. Such robots are also present in other medical robots as actuators. The literature shows that different methods are used to fabricate soft robots and employ them in different robotics tasks including positioning, grasping, and force exertion. Noticeably, such studies were done in robotics laboratories, dealing with robotics engineering problems. This review suggests that the technology is actively developing, but further focus on specific medical applications is required to fill the gap between soft robotics and its clinical use.

The Application of SLAM in Life and Scientific Research

This article mainly focuses on the application of SLAM in technology and provides a literature review on the following aspects: 1) The application of SLAM in automatic parking of automobiles. This includes using AVP-SLAM for high-precision automatic parking in outdoor parking lots using convolutional neural networks, and using MOFISLM for high-precision automatic parking when indoor GPS signals are poor. 2) The application of SLAM in robotics. It includes three aspects. The first is using the GMapping algorithm to construct and locate maps with high accuracy, low computational complexity, and high robustness, enabling robots to plan the shortest path in unknown environments. The second is to use ORB-SLAM2, which can handle more complex situations, to navigate medical institution robots to improve hospital efficiency and reduce disease transmission rates. The third is for robots that perform tasks in complex and unknown terrains. The improved version of LAMP1.0, LAMP2.0, which is suitable for complex underground environments, can achieve multi robot collaborative cooperation with high accuracy and robustness. 3) Application of SLAM in the field of unmanned aerial vehicles. This article mainly elaborates on four aspects. The first is to use visual SLAM to achieve collaborative work between ground robots and drones, and to utilize the high camera advantage of drones to quickly build maps for ground robots, improve accuracy, and save time. The second is to utilize the application of VSLAM on unmanned aerial vehicles to contribute to agriculture. The third is ORB-SLAM3 to provide rapid and high-precision landing on deck for unmanned aerial vehicles in maritime missions. The fourth is using SLAM to assist unmanned aerial vehicles in landing in emergency or position situations (such, when GPS signals are lost).

Scalable enforcement of geometric non-interference constraints for gradient-based optimization

Many design optimization problems include constraints to prevent intersection of the geometric shape being optimized with other objects or with domain boundaries. When applying gradient-based optimization to such problems, the constraint function must provide an accurate representation of the domain boundary and be smooth, amenable to numerical differentiation, and fast-to-evaluate for a large number of points. We propose the use of tensor-product B-splines to construct an efficient-to-evaluate level set function that locally approximates the signed distance function for representing geometric non-interference constraints. Adapting ideas from the surface reconstruction methods, we formulate an energy minimization problem to compute the B-spline control points that define the level set function given an oriented point cloud sampled over a geometric shape. Unlike previous explicit non-interference constraint formulations, our method requires an initial setup operation, but results in a more efficient-to-evaluate and scalable representation of geometric non-interference constraints. This paper presents the results of accuracy and scaling studies performed on our formulation. We demonstrate our method by solving a medical robot design optimization problem with non-interference constraints. We achieve constraint evaluation times on the order of 10-6\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$10^{-6}$$\\end{document} seconds per point on a modern desktop workstation, and a maximum on-surface error of less than 1.0% of the minimum bounding box diagonal for all examples studied. Overall, our method provides an effective formulation for non-interference constraint enforcement with high computational efficiency for gradient-based design optimization problems whose solutions require at least hundreds of evaluations of constraints and their derivatives.

ტექნოლოგიების გავლენა ჯანდაცვის სერვისების განვითარებაზე

Telemedicine gained a special impetus after the wide spread of information technology (IT). The use of information technology offers the healthcare industry a huge potential to solve its most important problem. The importance of using Industry 4.0 technologies in medicine is highlighted, which contributes to the introduction of digitalization elements in healthcare and medical services. The application areas and advantages of 3D printing, medical robots, Internet of Things, artificial intelligence are given. Phases of telemedicine development from the middle of the 19th century to modern times are given. Systematic use of Industry 4.0 tools will contribute to the correct clinical decisions, give the patient and the clinic adequate access to health records, improve the accuracy and reliability of these records, and contribute to the collection, systematization and analysis of quality service data. In this case, the joint use of such technologies as artificial intelligence, gene editing, advanced robotics, which have actually removed the previously existing boundaries between the physical, digital and biological worlds, is of crucial importance.

Features of Classification of Crimes Committed by Persons using Artificial Intelligence Technologies in Healthcare

Recognizing positive possibilities of artificial intelligence technologies in healthcare, as well as current ways to use them, the author identifies the main forms of implementation of digital innovation: physical form in the form of a medical robot and intellectual form in the form of software, registered as medical devices. It is stated that the legal issues related to bringing to justice for actions related to the use of intelligent systems in healthcare, which led to negative consequences, including harm to the life and health of patients, have yet to be resolved. According to the current legal regulation in Russia it is a medical organization and a medical professional using artificial intelligence systems or medical robotics equipped with digital technologies who are held liable for the harm caused to the life and (or) health of citizens while providing them with medical care. In turn, system developers, as well as those who train a system based on artificial intelligence (developers of artificial intelligence systems), are not held liable. The problems of classification of crimes committed by medical professionals using artificial intelligence technologies in healthcare are considered. A medical worker providing medical care using artificial intelligence may be the subject of a crime under Part 2 of Article 109 and part 2 of Article 118 of the Criminal Code of the Russian Federation, but not under Article 238 of the Criminal Code of the Russian Federation. In addition, the rules for the classification of crimes committed by other entities (the operator of information systems) using artificial intelligence technologies are formulated.

A Multi‐Module Sensing and Bi‐Directional HMI Integrating Interaction, Recognition, and Feedback for Intelligent Robots

AbstractRapid advances in robotics have placed urgent demands on more intelligent human‐machine interaction technologies. Specifically, the way of establishing dual‐way intuitive communication with a consistent sensory system can greatly enhance efficiency and reliability. Here, a bi‐directional human‐machine interface (HMI) is designed by applying starch‐based hydrogel sensors. The whole system consists of a multi‐modal wearable sensory exoskeleton with a haptic feedback module and sensory robotic hand. The sensory exoskeleton with strain‐sensing glove and rotation‐sensing arm can capture and project the motion of the entire upper limb. The system offers object recognition functions by utilizing a sensing array on the robotic hands and machine learning algorithms, which can identify the shape and hardness information. The recognized results can be delivered back to the operator via vision and vibrational haptic feedback, respectively. This dual‐way intelligent sensory system shows potential application in many key fields such as the Internet of Things, teleoperation, and medical robotics.

Robot, let us pray! Can and should robots have religious functions? An ethical exploration of religious robots

AbstractConsiderable progress is being made in robotics, with robots being developed for many different areas of life: there are service robots, industrial robots, transport robots, medical robots, household robots, sex robots, exploration robots, military robots, and many more. As robot development advances, an intriguing question arises: should robots also encompass religious functions? Religious robots could be used in religious practices, education, discussions, and ceremonies within religious buildings. This article delves into two pivotal questions, combining perspectives from philosophy and religious studies: can and should robots have religious functions? Section 2 initiates the discourse by introducing and discussing the relationship between robots and religion. The core of the article (developed in Sects. 3 and 4) scrutinizes the fundamental questions: can robots possess religious functions, and should they? After an exhaustive discussion of the arguments, benefits, and potential objections regarding religious robots, Sect. 5 addresses the lingering ethical challenges that demand attention. Section 6 presents a discussion of the findings, outlines the limitations of this study, and ultimately responds to the dual research question. Based on the study’s results, brief criteria for the development and deployment of religious robots are proposed, serving as guidelines for future research. Section 7 concludes by offering insights into the future development of religious robots and potential avenues for further research.

A study on the application of artificial intelligence in the design of intelligent medical robots

Abstract With the development of artificial intelligence and robotics technology, the combination of artificial intelligence and medical device research and development has been promoted, which is an important product of the development of artificial intelligence. In this paper, the general structure of the intelligent medical robot is designed by combining artificial intelligence technology and robotics-related technology. Then, the binocular vision function of the robot was realized by visually acquiring the image of the target object, 3D reconstruction of the target object, and combining the SIFT image recognition algorithm and target tracking algorithm. Then, a new speech recognition algorithm was constructed to realize the human-robot interaction function with the medical robot based on the deep learning Transforme network after the construction of the human acoustic model. Finally, the designed intelligent medical robot was tested, and its overall performance was evaluated. The results show that the recognition errors of the intelligent medical robot on the features of the items are all within 0.05, the recognition errors on the features of the human body are within 0.2, and the speed of the target tracking is between 6km/h and 16km/h. The average recognition accuracy of the medical robot for voice commands is about 0.9, the recognition time is about 0.7s, the normal working rate of each function is more than 0.99, and the test speed is within 2s.

Liquid Metal Functionalization Innovations in Wearables and Soft Robotics for Smart Healthcare Applications

AbstractSmart healthcare solutions are crucial for early diagnosis, real‐time health monitoring, and personalized therapy. Essential to these advancements are flexible wearable devices and medical robotics, which incorporate a range of elements, including soft sensors, therapeutic modules, human‐machine interfaces, actuators, and systems for communication, computation, and power. Liquid metal‐based materials are rapidly emerging as one of the key elements for these innovations. This review will delve into the latest breakthroughs in liquid metal (LM) functionalization innovation and the applications in healthcare‐related wearables and soft robotics. Firstly, techniques to modify LM are explored, emphasizing strategies to enhance properties such as electromechanical, thermal, electromagnetic, biochemical, self‐healing, and magnetic capabilities. Next, the authors shed light on contemporary wearable sensors, therapeutic on‐skin devices, and other flexible device innovations. They finally conclude by highlighting the challenges and charting the path forward for LM‐driven healthcare advances.

Research on Improved Dual Channel Medical Short Text Intention Recognition Algorithm

Abstract The increasing application of medical robots in the healthcare sector underscores the critical importance of intent recognition in enhancing the interaction and assistance capabilities of these robots. Traditional intent recognition methods utilize convolutional neural networks (CNNs) for text analysis but often fall short in capturing global features, resulting in incomplete information. To address this challenge, this paper introduces an innovative approach by combining an enhanced CNN with bidirectional gated recurrent units (BiGRU) to construct a dual-channel short-text intent recognition model. This model effectively leverages both local and global features to more accurately comprehend user needs and intentions. Experimental results demonstrate that this model excels, achieving an accuracy rate of 96.68% and an F1 score of 96.67% on the THUCNews_Title dataset. In comparison to conventional intent recognition models, it exhibits significantly improved performance, thereby providing substantial support for medical robots in patient care and assisting healthcare professionals.

Design and development of a fuzzy explainable expert system for a diagnostic robot of COVID-19

<p><span lang="EN-US">Expert systems have been widely used in medicine to diagnose different diseases. However, these rule-based systems only explain why and how their outcomes are reached. The rules leading to those outcomes are also expressed in a machine language and confronted with the familiar problems of coverage and specificity. This fact prevents procuring expert systems with fully human-understandable explanations. Furthermore, early diagnosis involves a high degree of uncertainty and vagueness which constitutes another challenge to overcome in this study. This paper aims to design and develop a fuzzy explainable expert system for coronavirus disease-2019 (COVID-19) diagnosis that could be incorporated into medical robots. The proposed medical robotic application deduces the likelihood level of contracting COVID-19 from the entered symptoms, the personal information, and the patient's activities. The proposal integrates fuzzy logic to deal with uncertainty and vagueness in diagnosis. Besides, it adopts a hybrid explainable artificial intelligence (XAI) technique to provide different explanation forms. In particular, the textual explanations are generated as rules expressed in a natural language while avoiding coverage and specificity problems. Therefore, the proposal could help overwhelmed hospitals during the epidemic propagation and avoid contamination using a solution with a high level of explicability.</span></p>

A Wearable Co-Located Neural-Mechanical Signal Sensing Device for Simultaneous Bimodal Muscular Activity Detection.

The co-located and concurrent measurement of both muscular neural activity and muscular deformation is considered necessary in many applications, such as medical robotics, assistive exoskeletons and muscle function evaluations. Nevertheless, conventional muscle-related signal perception systems either detect only one of these modalities, or are made with rigid and bulky components that cannot provide conformal and flexible interface. Herein, a flexible, easy-to-fabricate, bimodal muscular activity sensing device, which collects neural and mechanical signal at the same muscle location, is reported. The sensing patch includes a screen-printed sEMG sensor, and a pressure-based muscular deformation sensor (PMD sensor) based on a highly sensitive, co-planar iontronic pressure sensing unit. Both sensors are integrated on a super-thin (25 μm) substrate. The sEMG sensor shows a high signal-to-noise ratio of 37.1 dB, and the PMD sensor sensor exhibits a high sensitivity of 70.9 kPa -1. The responses of the sensor to three types of muscle activities (isotonic, isometric, and passive stretching) were analyzed and validated by ultrasound imaging. Bimodal signals during dynamic walking experiments with different level-ground walking speeds were also investigated. The application of the bimodal sensor was verified in gait phase estimation, and results show that the assembly of both modalities significantly reduce (p < 0.05) the average estimation error across all subjects and all walking speeds to 3.82%. Demonstrations show the potential of this sensing device for informative evaluation of muscular activities, and its abilities in human-robot interaction.