Healthcare Robots Research Articles

Application of Social Robots in Healthcare: Review on Characteristics, Requirements, Technical Solutions.

Cyber-physical or virtual systems or devices that are capable of autonomously interacting with human or non-human agents in real environments are referred to as social robots. The primary areas of application for biomedical technology are nursing homes, hospitals, and private homes for the purpose of providing assistance to the elderly, people with disabilities, children, and medical personnel. This review examines the current state-of-the-art of social robots used in healthcare applications, with a particular emphasis on the technical characteristics and requirements of these different types of systems. Humanoids robots, companion robots, and telepresence robots are the three primary categories of devices that are identified and discussed in this article. The research looks at commercial applications, as well as scientific literature (according to the Scopus Elsevier database), patent analysis (using the Espacenet search engine), and more (searched with Google search engine). A variety of devices are enumerated and categorized, and then our discussion and organization of their respective specifications takes place.

Highly Sensitive Temperature Detection Based on a Frost- and Dehydration-Resistive Ion-Doped Hydrogel-MXene Composite.

Wearable temperature sensors with high sensitivity and stability hold great potential for human health monitoring. However, hydrogels, which are commonly used for wearable devices, often show poor thermal and electrical conductivity and are susceptible to dehydration and freezing. Herein, we developed a frost- and dehydration-resistive temperature sensor based on Fe2+/Ti2CTx/κ-carrageenan (CA)-polyacrylamide (PAM) hydrogel. The Fe2+ ions within the hydrogel existed in two forms: as free ions and bonded ions. The free Fe2+ ions could complex with water molecules, resulting in the improved resistance to dehydration and freezing, as well as enhanced ionic conductivity in the hydrogel. On the other hand, the remaining Fe2+ ions acted as linkers to form coordination bonds with the sulfate groups of CA chains, resulting in the greatly enhanced mechanical strength of the hydrogel. In addition, the Ti2CTx nanosheet-based fillers formed a well-defined porous laminar structure, which reduced the phonon scattering and improved the phonon adsorption within the hydrogel. The Fe2+/Ti2CTx/CA-PAM hydrogel sensor exhibited excellent temperature sensing performance including a good linearity (R2 = 0.998) within a broad working range (-10 to 60 °C), high resolution (0.1 °C), and good repeatability. Furthermore, the sensor was integrated into a wireless system for continuous monitoring of body temperature, demonstrating its potential in healthcare monitoring, electronic skins, and intelligent robots.

Patients’ behavioral intentions toward robotic adoption in healthcare: An approach on apprehension of embedding robotics

The ubiquitous healthcare sector requires a variegated set of emerging innovations and advanced technologies in the healthcare sector. Healthcare stakeholders in a turbulent marketplace continuously strive to maintain relevance; thus, the healthcare robotics notion has emerged to become a game-changer in the human realm. These emerging systems provide new possibilities to create a core value for stakeholders, specifically care providers and care receivers, in the turbulent environment. Although robotics is moving forward in healthcare, human inertia and apprehension are still anchors exerting robotics. Human behaviors and attitudes may change with time and in different circumstances. This paper aims to contribute a new perspective to the patients’ degree of apprehensions—trust, ethical, privacy, and legal concerns—which affect their behavioral intentions toward robotics adoption in healthcare by considering the moderating effect of social crises, including the aging and COVID-19 pandemic. The brink of a robotic era is encountered with challenges, including the aging population and COVID-19 for public and private healthcare stakeholders worldwide. Hence, this study’s essential support is to investigate emerging technology adoption and hurdles to ascertain how the patients’ behavioral intentions might affect robotic adoption in healthcare. Furthermore, this paper examines the anchors’ factors that affect individual behavioral intentions to successfully propose remedies to embed robotics in the human realm. The results indicate that trust, privacy, and ethical concerns are direct predictors of behavioral intentions toward robotic adoption. Moreover, behavioral intentions toward robotics adoption significantly affect the actual use of robotics in the healthcare industry in the future. Furthermore, social inertia, including aging and pandemics, significantly and positively affects behavioral intentions toward healthcare robotic adoption and use. Finally, both aging and pandemic positive interactions affect actual robotic use in the future of the healthcare industry.

Design and control of an autonomous visitor guiding robot in a hospital environment (Viguro Robot)

In recent years, the development of autonomous robots for healthcare applications has gained significant interest. This paper presents the design and development of an autonomous robot tailored for guiding visitors in healthcare facilities, aiming to enhance their experience and provide efficient navigation. Equipped with huskylens cameras, proximity sensors, and other sensors, the robot perceives its environment and detects obstacles. A robust navigation system incorporates mapping and localization algorithms, enabling real-time mapping and accurate positioning. Through a user-friendly interface, visitors input their destination, and the robot plans an optimal path considering distance, obstacles, and congestion. It adapts to dynamic changes like moving objects or crowded areas for safe and efficient navigation. The development process involved iterative design, prototyping, and testing, incorporating feedback from staff and visitors for improved functionality and user experience. Preliminary pilot test results demonstrate the effectiveness of the autonomous guiding robot, providing accurate navigation and enhancing visitor satisfaction. This research contributes to advancing autonomous robotics in healthcare by addressing the need for visitor guidance, improving efficiency, potentially reducing staff workload, and enhancing overall experiences for patients and visitors.

525-P: Droid Audio Visual Educator–Diabetes Nutrition (DAVE-DN) Randomized Controlled Trial

Background: Worldwide, demand for health care services far outpaces the availability of staff. The use of robots in healthcare has advanced in recent years as robots are seen as a viable solution to address the shortage of healthcare staff. We propose the use of a humanoid robot to provide basic nutritional education to patients with diabetes in the waiting room, hence freeing up time for dieticians to address more complex issues. We hypothesize that use of this intervention will be more effective than the current standard of care i.e. A leaflet, in educating and empowering patients with diabetes. Methods: We conducted a single-centre, randomized controlled trial to determine whether a humanoid robot would improve patient’s knowledge of nutrition. The primary outcome of the trial is improvement in patient knowledge score based on 36 items from a validated nutrition questionnaire. Each patient’s prior knowledge of nutrition was assessed by a validated questionnaire prior to the intervention. Patients were randomized to current standard of care i.e. physician-led education plus a leaflet (n=40) or standard of care plus Droid Audio Visual Educator (n=40). Following the trial, both groups had their knowledge of nutrition reassessed using the same validated questionnaire. The performance of patients in each group was compared and effectiveness of the intervention in improving education objectively determined. Results: A total of 90 patients underwent randomization. 10 withdrew before completion. The mean age was 53.7 years. The change in score in the intervention group was 3.2 of 36 points higher than control group on average (95% confidence interval [CI] 0.9 to 5.4; P= 0.006). Conclusions: This trial suggests there is potential for humanoid robots to deliver basic nutritional education Disclosure S.O'connor: None. J.Ong: None. B.Lim: None. S.Coleman: None. H.Worlikar: None. C.Connolly: None. S.E.Mcgarel: None. T.O'brien: None. D.T.O'keeffe: None. Funding Health Services Executive, Intern Network Academic Track

Technological machines and artificial intelligence in nursing practice.

This article is a theoretical discourse about technological machines and artificial intelligence, highlighting their effective interactive outcomes in nursing. One significant influence is technological efficiency which positively affects nursing care time, enabling nurses to focus more on their patients as the core of nursing. The article examines the impact of technology and artificial intelligence on nursing practice in this era of rapid technological advancements and technological dependence. Strategic opportunities in nursing are advanced, exemplified by robotics technology and artificial intelligence. A survey of recent literature focused on what is known about the influence of technology, healthcare robotics, and artificial intelligence on nursing in the contexts of industrialization, societal milieu, and human living environments. Efficient, precision-driven machines with artificial intelligence support a technology-centered society in which hospitals and healthcare systems become increasingly technology-dependent, impacting healthcare quality and patient care satisfaction. As a result, higher levels of knowledge, intelligence, and recognition of technologies and artificial intelligence are required for nurses to render quality nursing care. Designers of health facilities should be particularly aware of nursing's increasing dependence on technological advancements in their practice.

3D printable resin/carbon nanotube composites for wearable strain sensors: Enhancing mechanical and electrical properties

Electrically conductive composite materials are widely used for several applications, particularly flexible strain sensors for wearable electronic devices to detect human motions or apply to soft robotic technologies. Among the carbon nanotube (CNT) composites for strain sensors, the CNT composites with polypyrrole (PPy) have been scarcely found for electromechanical property improvement via digital light processing (DLP) 3D printing. Thus, this research presents a 3D printing fabrication of flexible polyurethane/CNT/PPy (FPU/CNT/PPy) composites for high complexity and model specifications, particularly strain sensing. The FPU/CNT/PPy composites were prepared as photopolymer resin with various proportions of the three components. The composites successfully achieved a gauge factor of 91.9 at 20 percent strain with high durability in 100 stretching-releasing cycles. More than 85% of printing accuracy was also found under the DLP 3D printing method. The small deformation of the composites could be detected during the stretching-releasing process during time-dependent testing. Examples of simple human activity and complex spring motion could be successfully detected due to the high responsibility and reproducibility of the finger motion. The composites mentioned in this study could reach the field of strain sensing and can further be applied to other fields such as healthcare and soft robotics.

Artificial Intelligence With Robotics in Healthcare: A Narrative Review of Its Viability in India.

This short review focuses on the emerging role of artificial intelligence (AI) with robotics in the healthcare sector. It may have particular utility for India, which has limited access to healthcare providers for a large growing population and limited health resources in rural India. AI works with an amalgamation of enormous amounts of data using fast and complex algorithms. This permits the software to quickly adapt the pattern of the data characteristics. It has the possibility to collide with most of the facets of the health system which may range from discovery to prediction and deterrence.The use of AI with robotics in the healthcare sector has shown a remarkable rising trend in the past few years. Functions like assistance with surgery, streamlining hospital logistics, and conducting routine checkups are some of the tasks that may be managed with great efficiency using artificial intelligence in urban and rural hospitals across the country. AIin the healthcare sector is advantageous in terms of ensuring exclusive patient care, safe working conditions where healthcare providers are at a lower risk of getting infected, and perfectly organized operational tasks. As the healthcare segment is globally recognized as one of the most dynamic and biggest industries, it tends to expedite development through modernization and original approaches. The future of this lucrative industry is looking forward to a great revolution aiming to create intelligent machines that work and respond like human beings. The future perspective of AI and robotics in the healthcare sector encompasses the care of elderly people, drug discovery, diagnosis of deadly diseases, a boost in clinical trials, remote patient monitoring, prediction of epidemic outbreaks, etc. However, the viability of using robotics in healthcare may be questionable in terms of expenditure, skilled workforce, and the conventional mindset of people. The biggest challenge is the replication of these technologies to the smaller towns and rural areas so that these facilities may reach the larger segment of the entire population of the country. This review aims to examine the adaptability and viability of these new technologies in the Indian scenario and identify the major challenges.

Leveraging Automotive Innovations for Artificial Intelligence and Robotics in Healthcare

Integrating smart materials and autonomous systems from the automotive industry into healthcare is poised to revolutionize medical practices, particularly in diagnostics and surgical interventions. This article explores how innovations such as Shape Memory Alloys (SMA), Piezoelectric Materials, Electrochromic Materials, and Self-Healing Polymers, originally developed for automotive applications, can enhance the precision, safety, and efficiency of healthcare when combined with artificial intelligence (AI) and robotics. By drawing parallels between the automotive and healthcare industries, this review highlights key lessons in interoperability, safety, human-machine collaboration, and continuous improvement that can be applied to medical technologies. For instance, SMA-based surgical tools can adapt to complex anatomical structures guided by AI in real-time. At the same time, piezoelectric materials enable haptic feedback in robotic surgery, providing surgeons with a tactile sense of tissue interaction. Additionally, electrochromic smart surgical glasses can dynamically adjust tinting during procedures, and self-healing polymers ensure the durability of wearable health monitoring devices. These cross-industry innovations offer a pathway to more personalized, efficient, and reliable healthcare delivery. However, challenges remain in standardizing protocols, ensuring regulatory compliance, and fostering user acceptance. The article concludes that ongoing research, interdisciplinary collaboration, and a focus on scalability will be essential in fully realizing the potential of these technologies in healthcare.

The Use of Robotic Technology in the Healthcare of People above the Age of 65-A Systematic Review.

The integration of robots can help provide solutions in regards to the need for an increase in resources in healthcare. The aim of this review was to identify how robots are utilized in the healthcare of people who are over the age of 65 and how this population experiences interacting with healthcare robots. A systematic literature review with an integrated design was conducted. A literature search was performed in the electronic databases CINAHL via EBSCO, EMBASE, and Medline via Ovid. Content analysis was performed to assess the studies that were included in this review. A total of 14 articles were included. Participants in the studies included 453 older people ranging from 65 to 108 years of age. Nine of the studies focused on people with dementia or cognitive impairment. Seven studies included different types of socially assistive human-like robots, six of the studies included two different types of animal-like robots, and one study focused on a robotic rollator. The robots mainly served as social assistive- or engagement robots.

Ecofriendly Polymer–Graphene‐Based Conductive Ink for Multifunctional Printed Electronics

AbstractThe ongoing research on printed and flexible electronics is primarily focused on conductive three‐dimensional (3D) print patterning. However, due to the nonhomogeneous distribution of conductive elements in a polymer matrix and their tendency to shrink, 3D‐printed patterns often suffer from low‐printing accuracies and poor mechanical and electrical properties. Herein, poly(vinyl butyral‐co‐vinyl alcohol‐co‐vinyl acetate) (PVBVA) is reinforced with microwave‐exfoliated graphene to develop a conductive ink for 3D printing. Compared with the pure PVBVA patterns, the PVBVA/graphene patterns exhibit a high‐electrical conductivity, a twofold enhancement in tensile strength, an improved printing accuracy, and a high stability because of the graphene addition. The PVBVA/graphene inks flow well during the printing; loading of up to 0.1 wt% graphene in the PVBVA gel results in notable changes in the rheological properties of the ink. The printed conductive patterns show a high flexibility suitable for wearable electronics. Additionally, multifunctional electronic operations such as photoinduced heating, temperature sensing, and motion sensing are possible. This study may pave the way for the development of a new class of smart wearable electronics for healthcare and soft robotics.

How Engineers’ Imaginaries of Healthcare Shape Design and User Engagement: A Case Study of a Robotics Initiative for Geriatric Healthcare AI Applications

In the development of robotics and Artificial Intelligence (AI) for healthcare, human-centered approaches seek to meet the requirements of healthcare practice and address social and ethical aspects proactively. In this work, an important but neglected aspect of human-computer interaction (HCI) is how engineers understand and envision the healthcare context. Drawing on insights from STS on engineers’ imaginaries and their role in shaping research and development of new technologies, we propose engineers’ imaginaries of healthcare as a point of analysis and intervention for ethical and social aspects of AI and robotics for healthcare. To illustrate the utility of this lens, we use it to on report a case study of an engineering project that develops robotic and AI applications for healthcare. We followed and sought to advance an embedded ethics and social science approach, where ethicists and social scientists accompanied this engineering project using direct interdisciplinary collaboration, observations, and in-depth qualitative interviews with the project’s engineers (n = 18). We analyze how the engineers imagine healthcare as an environment for robots, healthcare workers as potential users, and healthcare practices, and how these imaginaries connect to the design narratives that guide their work. Our findings provide pertinent input for HCI, STS, and engineering ethics related to healthcare AI and robotics, as they speak to prevalent narratives of “assistance” systems, aspects of how human healthcare practices are reframed and valued in the face of new technologies, questions of division of labor between machines and healthcare practitioners, and the implications of ‘acceptance’ as a frame for user-centered design.

Staying Informed of Best Evidence to Guide Practice

Staying Informed of Best Evidence to Guide Practice

Coaxial Graphene/MXene Microfibers with Interfacial Buffer-Based Lightweight Distance Sensors Assisting Lossless Grasping of Fragile and Deformable Objects.

Lossless and efficient robotic grasping is becoming increasingly important with the widespread application of intelligent robotics in warehouse transportation, human healthcare, and domestic services. However, current sensors for feedback of grasping behavior are greatly restricted by high manufacturing cost, large volume and mass, complex circuit, and signal crosstalk. To solve these problems, here, we prepare lightweight distance sensor-based reduced graphene oxide (rGO)/MXene-rGO coaxial microfibers with interface buffer to assist lossless grasping of a robotic manipulator. The as-fabricated distance microsensor exhibits a high sensitivity of 91.2 m-1 in the distance range of 50-300 μm, a fast response time of 116 ms, a high resolution of 5 μm, and good stability in 500 cycles. Furthermore, the high-performance and lightweight microsensor is installed on the robotic manipulator to reflect the grasp state by the displacement imposed on the sensor. By establishing the correlation between the microsensing signal and the grasp state, the safe, non-destructive, and effective grasp and release of the target can be achieved. The lightweight and high-powered distance sensor displays great application prospects in intelligent fetching, medical surgery, multi-spindle automatic machines, and cultural relics excavation.

The Effects of Healthcare Robot Empathy Statements and Head Nodding on Trust and Satisfaction: A Video Study

Clinical empathy has been associated with many positive outcomes, including patient trust and satisfaction. Physicians can demonstrate clinical empathy through verbal statements and non-verbal behaviors, such as head nodding. The use of verbal and non-verbal empathy behaviors by healthcare robots may also positively affect patient outcomes. The current study examined whether the use of robot verbal empathy statements and head nodding during a video recorded interaction between a healthcare robot and patient improved participant trust and satisfaction. One hundred participants took part in the experiment, online through Amazon Mechanical Turk. They were randoimnized to watch one of four videos depicting an interaction with a `patient' and a Nao robot that (1) either made empathetic or neutral statements, and (2) either nodded its head when listening to the patient or did not. Results showed that the use of empathetic statements by the healthcare robot significantly increased participant perceptions of robot empathy, trust and satisfaction, and reduced robot distrust. No significant findings were revealed in relation to robot head nodding. The positive effects of empathy statements support the model of Robot-Patient Communication, which theorizes that robot use of recommended clinical empathy behaviors can improve patient outcomes. The effects of healthcare robot nodding behavior needs to be further investigated.

Socially assistive robots in health and social care: Acceptance and cultural factors. Results from an exploratory international online survey.

This study explored the views of an international sample of registered nurses and midwives working in health and social care concerning socially assistive robots (SARs), and the relationship between dimensions of culture and rejection of the idea that SARs had benefits in these settings. An online survey was used to obtain rankings of (among other topics) the extent to which SARs have benefits for health and social care. It also asked for free text responses regarding any concerns about SARs. Most respondents were overwhelmingly positive about SARs' benefits. A small minority strongly rejected this idea, and qualitative analysis of the objections raised by them revealed three major themes: things might go wrong, depersonalization, and patient-related concerns. However, many participants who were highly accepting of the benefits of SARs expressed similar objections. Cultural dimensions of long-term orientation and uncertainty avoidance feature prominently in technology acceptance research. Therefore, the relationship between the proportion of respondents from each country who felt that SARs had no benefits and each country's ratings on long-term orientation and uncertainty avoidance were also examined. A significant positive correlation was found for long-term orientation, but not for uncertainty avoidance. Most respondents were positive about the benefits of SARs, and similar concerns about their use were expressed both by those who strongly accepted the idea that they had benefits and those who did not. Some evidence was found to suggest that cultural factors were related to rejecting the idea that SARs had benefits.

Flexible Plasmonic Optical Tactile Sensor for Health Monitoring and Artificial Haptic Perception

AbstractTactile sensors capable of quantifying mechanical stimuli through physical contact play a pivotal role in healthcare, prosthetics, and humanoid robotics. To enable conformal contact with objects of different surface morphologies, tactile sensors with high mechanical flexibility are extensively explored. Despite recent advances, most of the currently available flexible tactile sensors are based on electrical properties of functional materials, which often suffer from intrinsic limitations such as hysteresis, parasitic effects and electromagnetic interference. Herein, a flexible optical tactile sensor is presented by harnessing the unique optical properties of a soft and plasmonic optical fiber, made from composites of gold nanoparticles and elastomers. The tactile sensor is constructed by assembling the nanocomposite fiber in a sandwich structure, where sensitive and instantaneous sensing of contact force with high precision, low hysteresis, and tunable sensitivity is achieved by transducing mechanical stimuli into interpretable light signals. As demonstrations of its potential, the tactile sensor is utilized for real‐time monitoring of blood pressure, respiration, as well as providing tactile mapping of diverse hand motions. To further verify the feasibility of mimicking tactile perception of human skin, the proposed sensors integrated onto a robotic hand are demonstrated to perceive hardness, roughness, and shape of objects.

Tutorial on memristor-based computing for smart edge applications

Smart computing on edge-devices has demonstrated huge potential for various application sectors such as personalized healthcare and smart robotics. These devices aim at bringing smart computing close to the source where the data is generated or stored, while coping with the stringent resource budget of the edge platforms. The conventional Von-Neumann architecture fails to meet these requirements due to various limitations e.g., the memory-processor data transfer bottleneck. Memristor-based Computation-In-Memory (CIM) has the potential to realize such smart edge computing for data-dominated Artificial Intelligence (AI) applications by exploiting both the inherent properties of the architecture and the physical characteristics of the memristors. This paper discusses different aspects of CIM, including classification, working principle, CIM potentials and CIM design-flow. The design-flow is illustrated through two case studies to demonstrate the huge potential of CIM in realizing orders of magnitude improvement in energy-efficiency as compared to the conventional architectures. Finally future challenges and research directions of CIM are covered.

Robots in Healthcare

research-article Share on Robots in Healthcare Author: Rae Yule Kim Montclair State University Montclair State UniversityView Profile Authors Info & Claims InteractionsVolume 30Issue 1January - February 2023 pp 48–51https://doi.org/10.1145/3575871Published:11 January 2023Publication History 0citation70DownloadsMetricsTotal Citations0Total Downloads70Last 12 Months70Last 6 weeks70 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Transformation of the Physician-patient Relationship: From Bioethics to Roboethics

In the context of the active development and implementation of artificial intelligence systems and robotics in healthcare, the physician-patient relationship is undergoing changes. The transformation of these relations caused by the problems of interrelation of the basic bioethical principles and new approaches to the diagnosis and treatment of diseases is considered. Using concrete examples, new opportunities and risks caused by the widespread use of automation in medicine are revealed. Conflict situations between human norms and algorithms are analyzed. The issues of responsibility for robot errors, as well as privacy and cybersecurity issues are considered. It is noted that by the beginning of the 21st century, there was a need for an ethical assessment of robotics, since technical decisions taken in the design of robots have the potential to directly and significantly affect people's lives. In this regard, roboethics arose, the concept of which is analyzed in the article. The laws of robotics were formulated by I. Asimov and F. Pasquale. At the same time, attention is drawn to the fact that in the field of healthcare, programs should be developed that rely on human strength. The necessity of finding a balance between the automation of medical practice and the maintenance of the humanistic essence of the physician-patient relationship is emphasized. A comparative analysis of the fundamental principles of bioethics and roboethics is carried out. Despite the fact that they have the same goals and values, in roboetics these principles are characterized by a number of features. The principle related only to roboethics — explainability — requires algorithm developers to explain the general rationale and methodology for solving artificial intelligence. In conclusion, it is concluded that medical robotics and artificial intelligence systems provide great prospects for improving diagnosis, treatment and the general level of medical care, but their use raises important ethical issues that need to be addressed. The basic principles of bioethics should be preserved, and roboethics can help to define the framework and standards for the use of robots in medical practice.