Healthcare Robots Research Articles

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.

Ethics and Accountability of Care Robots

The subject of this paper is ethical and responsibility issues relating to the development and acquisition of robotics in healthcare. The purpose of the paper is to study previous scientific publications and research related to the topic and to clarify which questions, aspects, and concerns are most relevant when considering ethics and responsibility issues related to care robots. In the second phase, ideas from different stakeholders regarding the viewpoints are studied, and those ideas are compared to the ones presented in previous publications. The aim of this study is to find solutions to the issues presented in scientific literature and, also, to find new issues for consideration and further studies. The study is qualitative, and a theme interview was utilized as the main method for acquiring knowledge. The study is a part of the SHAPES Horizon 2020 project. From the perspective of SHAPES, the aim of the study is to provide useful knowledge for the project, which would in part promote the goal of SHAPES, i.e., the development of an international healthcare ecosystem. Based on the results of the study, it can be argued that the issues presented in previous academic publications regarding the ethics and accountability of robots in practical healthcare work are not relevant. Both the legislation and the logic of the AI algorithms used by care robots prevent those situations presented in previous academic discussions in which robots would presumably be forced to make decisions demanding ethical consideration. The results also point toward the fact that current legislation does not limit the development of healthcare robots more than it limits healthcare work in general. Thus, the considerations of ethics regarding care robots should rather be focused on the threshold values used by robots, when making interpretations, as well as the data used for the purpose of machine learning. These were identified as potential subjects for further research.

Ethics and Accountability of Care Robots

The subject of this paper is ethical and responsibility issues relating to the development and acquisition of robotics in healthcare. The purpose of the paper is to study previous scientific publications and research related to the topic and to clarify which questions, aspects, and concerns are most relevant when considering ethics and responsibility issues related to care robots. In the second phase, ideas from different stakeholders regarding the viewpoints are studied, and those ideas are compared to the ones presented in previous publications. The aim of this study is to find solutions to the issues presented in scientific literature and, also, to find new issues for consideration and further studies. The study is qualitative, and a theme interview was utilized as the main method for acquiring knowledge. The study is a part of the SHAPES Horizon 2020 project. From the perspective of SHAPES, the aim of the study is to provide useful knowledge for the project, which would in part promote the goal of SHAPES, i.e., the development of an international healthcare ecosystem. Based on the results of the study, it can be argued that the issues presented in previous academic publications regarding the ethics and accountability of robots in practical healthcare work are not relevant. Both the legislation and the logic of the AI algorithms used by care robots prevent those situations presented in previous academic discussions in which robots would presumably be forced to make decisions demanding ethical consideration. The results also point toward the fact that current legislation does not limit the development of healthcare robots more than it limits healthcare work in general. Thus, the considerations of ethics regarding care robots should rather be focused on the threshold values used by robots, when making interpretations, as well as the data used for the purpose of machine learning. These were identified as potential subjects for further research.

A Note on Reinforcement Learning

In the past decade, deep reinforcement learning (DRL) has drawn much attention in theoretical research, meanwhile, it has seen huge success across multiple application areas, such as combinatorial optimization, recommender systems, autonomous driving, intelligent healthcare system and robotics. As one of three basic machine learning paradigms, reinforcement learning concerns with how intelligent agents learn in an interactive environment through trial and error to maximize the total cumulative reward of the agents. Even though many progresses of reinforcement learning have been presented, there are still many challenging research topics due to the complexity of the problems.

Engaging citizen stakeholders on the topic of social robotics in healthcare

Engaging citizen stakeholders on the topic of social robotics in healthcare

Significance and Application of Robotics in the Healthcare and Medical Field

Technologies have a great impact on the Healthcare and medical sectors as this helps the professionals to boost their productivity and efficiency to a great extent. Robotics has a great influence on the entire activity of the health care sector and this has the capability of changing the entire workflow. With the assistance of robotics and artificial intelligence HealthCare professionals upgrade their day to day operation and provide best patient care for the betterment and first recovery of the patient. In the majority of cases robots are eventually used to make the surgeries and the recovery of the patient more effective and impactful. On the other hand, this also has the pharmaceutical and other Healthcare systems to meet the demand of the market place with the help of enhanced productivity and efficiency. Despite the advantages there are a number of different challenges and disadvantages are also involved with the overall implication of robotics in the healthcare and medical field. The challenges which are associated with the application of robotics in healthcare have been discussed critically within the study. The process to mitigate issues and avail most significant assistance through robotics in the medical sector has also been discussed with the entire study. Keyword : Robotics, healthcare, productivity, efficiency

Utilization of Robotics for Healthcare: A Scoping Review

Robotics is a disruptive technology that has already revolutionized patient healthcare globally. This technology is presently helping to perform various essential tasks such as conducting operations via numerous specializations and managing the entire operating room. Robot surgery is, in reality, available worldwide for knee substitution, correction of the hernia, and colon resection. Surgical robots entered the operating theatres far before entering other medicine-related robotics applications and now facilitate better outcomes for a whole range of healthcare products. In the COVID-19 pandemic, some robots were used in hospitals to deliver medicines, screen, perform odd jobs, and maintain hygienic conditions. This paper provides an overview about robotics and its various applications useful for healthcare. Significant enhancement, quality services, and advancements in healthcare services are also discussed. Here, we have identified the role of robotics in healthcare as a technology that dramatically changes the healthcare field. An artificial intelligence robot can duplicate creativity via algorithms, and its programming too plays a crucial role. Hospitals can now save time and money by removing the need for physical chores for different jobs. It is helpful for surgical training, exoskeletons, intelligent prostheses and bionics, robotic nurses, treatment, medicines, logistics, telepresence, and cleaning services. Robotics technologies such as gesture control, machine view, voice recognition, and touch sensor technology are also available. The future is bright with lower installation and maintenance costs.

Functional Epoxy Elastomer Integrating Self-Healing Capability and Degradability for a Flexible Stretchable Strain Sensor.

With the rapid development of flexible electronics and the increasing deterioration of the natural environment, functional and environmentally friendly flexible strain sensors have become one of the frontier research hotspots. Here, we propose a novel strategy to synthesize a functional epoxy elastomer integrating self-healing capability and degradability for flexible stretchable strain sensors. A carboxyl-terminated epoxy prepolymer was first synthesized using carboxyl-terminated PEG (PEG-COOH), 2,2'-dithiodibenzoic acid (DTSA), and 1,4-butanediol diglycidyl ether (BDDE), and then crosslinked by epoxidized soybean oil (ESO) to yield an epoxy elastomer. The obtained elastomer exhibited not only high tensile stress (5.07 MPa), large stretchability (477%), and high healing efficiency (92.5%) but also superior degradability in alkaline aqueous solution. The elastomer-based stretchable strain sensor with microstructure showed high sensitivity (GF = 176.71) and was successfully applied for detecting human motions and recognizing objects with various shapes. Moreover, the healed sensor could restore stable sensing ability. The prepared functional epoxy elastomer is of great significance for the preparation of environmentally friendly and high-performance sensors and is promising for applications in the fields of healthcare monitoring, intelligent robots, and wearable electronics.

The Politics of User-Driven Innovation: On innovative users, do-able needs, and frugal robots

Users play an increasingly important role in European innovation policy. They are commonly seen as drivers of and active co-creators within innovation processes. However, user-driven innovation remains infused with a number of assumptions about users, technology, and “successful” innovation, which (partly) undermine a more democratic, open approach to innovation. In this contribution, I investigate the interplay between broader policy assumptions in the European discourse on user-driven innovation and its practical performance within an innovation project centring on healthcare robotics. Here, I argue that the politics of user-driven innovation harbours particular assumptions that, in effect, restrict the agency of users while also engendering conflict and contradictory outcomes. Hence, user-driven innovation is not simply about users driving innovation but rather about interfacing users and their concerns with (robotics) developers and their technology. For this, I propose an analytics of interfacing, which draws together literatures on the performative dynamics of participatory processes and more recent work on the political economy of participation. Here, I contend that it is not enough to investigate the construction and performance of publics; rather, it is additionally necessary to follow the manifold practices by which those publics are rendered available for certain technological solutions – and vice versa. Such an analytical approach opens up a fruitful avenue to critically enquire into the politics of participation – sitting in between innovation policy and practice.