Healthcare Robots Research Articles

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.

Artificial Intelligence in Addressing Cost, Efficiency, and Access Challenges in Healthcare

Objective: The healthcare industry is undergoing a transformative phase marked by rising costs and a shortage of healthcare professionals, necessitating the adoption of information technology-based solutions (Shaheen, 2021). Methods: This study explores the integration of artificial intelligence (AI) in addressing these challenges and enhancing healthcare systems. Using a systematic literature review, we examined the role of AI in overcoming issues such as limited access, high costs, inefficiencies, and an aging population (Greenberg et al., 2020; Maphumulo & Bhengu, 2019). Our analysis focused on applications of AI in drug discovery, clinical trials, and patient care, including intelligent care systems and healthcare robotics (Chan et al., 2019; Vaishya et al., 2020). Results: The findings suggest that AI significantly accelerates drug discovery, streamlines clinical trials, and improves patient outcomes through advanced diagnostics and treatment support (Díaz et al., 2019; Woo, 2019). AI has proven particularly effective during the COVID-19 pandemic, where it aided in diagnosis, contact tracing, and treatment decision-making, highlighting its potential to address existing vulnerabilities in healthcare systems (Pavli et al., 2021). Conclusion: AI offers a paradigm shift in healthcare by providing clinicians with real-time access to robust clinical evidence and best practices, reducing reliance on anecdotal experience and cognitive biases (McNeill & Walton, 2002; Shaheen, 2021a). By harnessing the power of AI, healthcare systems can improve efficiency, reduce costs, and enhance patient outcomes, marking a significant step towards a more efficient, effective, and equitable healthcare system (Mayorga-Ruiz et al., 2019; Luengo-Oroz et al., 2020).

Comparative analysis of facial emotion recognition

This paper provides an overview of the phases, methods, and datasets used in modern Facial Emotion Recognition (FER). FER has been a crucial topic in computer vision and Machine Learning (ML) for decades. By using Convolutional Neural Networks (CNN) to recognize facial expressions, valuable insights into people's emotional states can be gained, leading to improved services such as personalized healthcare, enhanced customer service, and more effective marketing. Automated FER can be used in various settings, including healthcare, education, criminal investigations, and Human Robot Interface (HRI). The study includes a comparative analysis of the performance and conclusions of several models such as Visual Geometry Group 16 (VGG16), Residual Network 50 (ResNet50), MobileNet, Deep CNN and the proposed pretrained VGG 16 architecture. These models can be integrated into different systems for various purposes such as obtaining feedback on products, services, or virtual learning platforms. Ultimately, Facial Emotion Recognition using Convolutional Neural Networks (CNN) can help reduce bias in decision-making processes by providing an unbiased assessment of a person's emotional state.

Could Robots Empatize? A Review on The Employment of Social Robots in Mental Healthcare

The advances in artificial intelligence and robotics began to transform business and human relations. The employment of robots in health, education, entertainment and rehabilitation as well as industries introduced the concept of "social robots". Although there is no consensus on the definition of the concept, robots with some degree of autonomy and could conduct meaningful social interactions with humans are considered social robots. Studies have been conducted on the employment of social robots in mental health services. Studies have been conducted on the employment of social robots in mental health services. The effectiveness of social robots in the treatment of anxiety, stress, depression, anger, and eating disorders, especially dementia and autism spectrum disorder, has also been investigated. The question of “can robots empathize” is a significant topic in research that focus on human-robot interactions. Robotic empathy studies were conducted with two dimensions of human empathy for robots and robot empathy for humans and led to various philosophical and ethical discussions. Some argued that robot-human interaction leads to new opportunities in mental health services, while others criticized the use of robots since it could increase human solitude, blur the line between reality and virtuality perceptions and the distinction between ontological categories. The present literature review aimed to discuss the concepts of artificial intelligence, robots, and social robots, provide information about the studies on the employment of social robots in mental healthcare, and address the studies and views based on the question "can social robots empathize?"

The Use of Robotics in Healthcare

The present work aims, along the presented contents, to emphasize the use of robots within health, promoting assistance and assistance to health professionals, and highlighting which processes can be consolidated with the use of technology. The general objective of the research is to highlight the main aspects of the use of robotics in the health area, regarding the specific objectives, they are: to highlight the positive and negative aspects of the use of robotics in health; assess how health professionals use robots in their routines; present the researchers’ view on robotic procedures in health. In the methodological field, a literature review was carried out, highlighting some of the main concepts and addressing the vision of renowned authors on the process of inclusion of technology within health organizations. It can be concluded that technology promotes the understanding of relevant points so that treatments, processes and diagnoses are performed more effectively by health professionals.

Robotics in Sri Lanka: Current Status and Future Potential

Sri Lanka is a technological leader around the globe. As a result, Sri Lanka’s software sector is conducting several trials with Artificial intelligence, machine learning, and the Internet of Things. This study places an emphasis on the application of artificial intelligence in a major domain, robotics, which will have a significant impact in Sri Lanka in the near future. Starting from an introduction to the robotics domain in Sri Lanka, we discuss what is robotics, the impact of robotics in the world, and Sri Lanka in brief. This paper examines the current state of robotics in Sri Lanka, with a focus on its potential for economic and technological development. We review the existing research and development initiatives in robotics and identify the key challenges and opportunities facing the field in Sri Lanka. We also discuss the potential applications of robotics in various sectors, including manufacturing, agriculture, healthcare, and education. Through a review of the literature and interviews with industry experts, we aim to provide a comprehensive overview of the current state and future prospects of robotics in Sri Lanka. The most important and popular robotics implementations are selected and further analyzed. Then the significance and contribution of those two studies to robotics are analyzed with advantages and disadvantages for robotics domain in Sri Lanka. Next, the technologies and key algorithms are discussed in light of recent research. Finally concludes with future works and robotics barriers in Sri Lanka.

Robotlar Empati Yapabilir mi? Sosyal Robotların Ruh Sağlığı Hizmetlerinde Kullanımı Üzerine Bir Derleme

The advances in artificial intelligence and robotics began to transform business and human relations. The employment of robots in health, education, entertainment and rehabilitation as well as industries introduced the concept of "social robots". Although there is no consensus on the definition of the concept, robots with some degree of autonomy and could conduct meaningful social interactions with humans are considered social robots. Studies have been conducted on the employment of social robots in mental health services. Studies have been conducted on the employment of social robots in mental health services. The effectiveness of social robots in the treatment of anxiety, stress, depression, anger, and eating disorders, especially dementia and autism spectrum disorder, has also been investigated. The question of “can robots empathize” is a significant topic in research that focus on human-robot interactions. Robotic empathy studies were conducted with two dimensions of human empathy for robots and robot empathy for humans and led to various philosophical and ethical discussions. Some argued that robot-human interaction leads to new opportunities in mental health services, while others criticized the use of robots since it could increase human solitude, blur the line between reality and virtuality perceptions and the distinction between ontological categories. The present literature review aimed to discuss the concepts of artificial intelligence, robots, and social robots, provide information about the studies on the employment of social robots in mental healthcare, and address the studies and views based on the question "can social robots empathize?"

Heterogeneity of Attitudes toward Robots in Healthcare among the Chinese Public: A Latent Profile Analysis

Attitudes are deemed critical psychological variables that can determine end users' acceptance and adoption of robots. This study explored the heterogeneity of the Chinese public's attitudes toward robots in healthcare and examined demographic characteristics associated with the derived profile membership. The data were collected from a sample of 428 Chinese who participated in an online survey. Latent profile analysis identified three distinct subgroups regarding attitudes toward robots-optimistic (36.9%), neutral (47.2%), and ambivalent (15.9%). Interestingly, although participants in the ambivalent attitude profile held more negative attitudes toward interaction with or social influence of healthcare robots, their attitudes tended to be positive when it came to emotional interactions with healthcare robots. All the respondents reported negative attitudes toward the social influence of healthcare robots. Multivariable regression analysis results showed that there were significant differences in age, education level, monthly income, experience with computers, experience with wearable devices, and whether to follow robot-related news or not. This study confirmed the heterogeneity of the Chinese public's attitudes toward robots in healthcare and highlighted the importance of emotional interaction with and social influence of healthcare robots, which might facilitate a better understanding of the needs and expectations of potential end users for robots in healthcare to make them more acceptable in different situations.

Nursing and human-computer interaction in healthcare robots for older people: An integrative review.

This study examined the published works related to healthcare robotics for older people using the attributes of health, nursing, and the human-computer interaction framework. An integrative literature review. A search strategy captured 55 eligible articles from databases (CINAHL, Embase, IEEE Xplore, and PubMed) and hand-searching approaches. Bibliometric and content analyses grounded on the health and nursing attributes and human-computer interaction framework were performed using MAXQDA. Finally, results were verified using critical friend feedback by a second reviewer. Most articles were from multiple authorship, published in non-nursing journals, and originating from developed economies. They primarily focused on applying healthcare robots in practice settings, physical health, and communication tasks. Using the human-computer interaction framework, it was found that older adults frequently served as the primary users while nurses, healthcare providers, and researchers functioned as secondary users and operators. Research articles focused on the usability, functionality, and acceptability of robotic systems. At the same time, theoretical papers explored the frameworks and the value of empathy and emotion in robots, human-computer interaction and nursing models and theories supporting healthcare practice, and gerontechnology. Current robotic systems are less anthropomorphic, operated through real-time direct and supervisory inputs, and mainly equipped with visual and auditory sensors and actuators with limited capability in performing health assessments. Results communicate the need for technological competency among nurses, advancements in increasing healthcare robot humanness, and the importance of conscientious efforts from an interdisciplinary research team in improving robotic system usability and utility for the care of older adults.

Changing the Perceived Views of Student Nurses Concerning Healthcare Robots: A Video Intervention Approach.

Changing the Perceived Views of Student Nurses Concerning Healthcare Robots: A Video Intervention Approach.

Cognitively Assistive Robots at Home: Translating Clinical Interventions to Robots.

Much research in healthcare robotics explores extending rehabilitative interventions to the home. However, for adults, little guidance exists on how to translate human-delivered, clinic-based interventions into robot-delivered, home-based ones to support longitudinal interaction. This is particularly problematic for neurorehabilitation, where adults with cognitive impairments require unique styles of interaction to avoid frustration or overstimulation. For the past several years, our team has worked with neuropsychologists to develop cognitively assistive robots (CARs) that administer compensatory cognitive training (CCT) autonomously and longitudinally to people with mild cognitive impairment (PwMCI) at home. Our system helps users practice cognitive strategies to strengthen skills such as attention, learning/memory, and executive functioning. We explore the design of robot-delivered neurorehabilitation interventions for PwMCI. We used these prototypes as design probes to understand how neuropsychologists (n=6) envision translating CCT to a CAR, and features the robot intervention needs to be successful, such as supporting goal setting, content personalization, encouragement for real-world transfer, and ways to longitudinally maintain engagement. We also conducted interviews with PwMCI (n=3), the end users of the robot-administered intervention. We report our findings and specify design patterns and considerations for translating neurorehabilitation interventions to robots. First, we provide insights for translating neurorehabilitation interventions to CARs in order to contextualize them to the lives of PwMCI. Second, we present new interaction design patterns for robot-delivered neurorehabilitation interventions to maintain longitudinal engagement and intervention efficacy. Finally, we propose design considerations for developing robots for PwMCI, a population with unique needs and abilities distinct from those of people with dementia and older adults [1]. This work will serve as a basis for future endeavors to translate cognitive training and other clinical interventions onto a robot, support longitudinal engagement with home-deployed robots, and ultimately extend the accessibility of longitudinal health interventions for people with cognitive impairments. [1] Kubota, A., Cruz-Sandoval, D., Kim, S., Twamley, E., and Riek, L.D. "Cognitively Assistive Robots at Home: HRI Design Patterns for Translational Science." In Proceedings of the 17th Annual ACM/IEEE Conference on Human Robot Interaction (HRI). 2022.

Effects of Voice and Lighting Color on the Social Perception of Home Healthcare Robots

The influence of matching between robots’ social cues on users’ social perceptions should be investigated systematically to better fit robots to their occupational roles. In this study, an experiment with 69 older and middle-aged participants was conducted to explore the effects of the voice and lighting color of a home healthcare robot on users’ social perception, which was measured by the Robotic Social Attributes Scale (RoSAS). The results indicated that voice and lighting color significantly affected social perceptions of the healthcare robot. Specifically, the adopted robot received high warmth ratings when it had an adult female voice or a child voice, whereas it received high competence ratings when it had an adult male voice. The robot received a high warmth rating and a high competence rating when warm and cool lighting were used, respectively, as visual feedback. Furthermore, a mismatch in the robot’s voice and lighting color was discovered to evoke feelings of discomfort. The findings of this study can be used as a reference to design robots with acceptable social perception and to expand the roles of social robots in the future.

Application of Robotics in Healthcare and Surgery

The introduction of robotics into the medical field has opened a new door for precision, efficiency, and patient care. Systems like the da Vinci Surgical System have given surgeons an unmatched source of accuracy to perform complex procedures with. Evasiveness is minimized and recovery times are quicker than ever before. By using telemedicine robots, doctors are able to consult patients remotely and keep an eye on their condition too. Rehab becomes easier for patients with robotic exoskeletons that help them regain mobility and strength. Automation in pharmacies also aids in medication dispensing by removing human error from the equation. Finally, there are plenty of robots designed specifically for cleaning hospitals.
 Robots aren’t confined to doctor’s offices though. There are a number of different tasks they can complete that benefit patients directly. This ranges from providing medication reminders to offering companionship when no one else is available. Laboratories can cut down time to diagnose diseases by relying on AI technology which speeds up the process and gives it more precision. With all these different angles being attacked, it’s safe to say that healthcare is getting a much-needed upgrade thanks to robots. Assistants replacing manpower not only solves some problems but creates new ones as well. It seems as if every large-scale industry is being hit by automation in some way or another and this is no exception for healthcare. Although patients get better treatment at lower costs there’s one big problem: jobs are being lost left and right.