Care Robots Research Articles

Playful framings of social robots in dementia care: reconsidering the principle of transparency in interactions with robot animals

Abstract Research on social robots in dementia care has focused on their effects, for example in relation to the patients’ wellbeing or the care-givers’ working environment. Such approaches to social robots treat them as stable objects with a singular function. Combining social gerontology with social studies of science, the current study offers a new angle by asking: How do patients and care-givers in care homes for older people establish a shared definition of the situation in interactions involving robot animals? Drawing on ethnography and multimodal conversation analysis of 211 minutes of video recordings in two care homes in Sweden, we demonstrate the embodied work by which participants in interactions establish activities with robot animals. In contrast to the ideal of transparency in social robotics, we show that a central affordance of the robots is their vagueness, which allows for their inclusion in playful interactions. Playful framings of the robots highlight their social functions and downplay care-giver–patient asymmetries. However, situations where patients resist a playful frame actualise a dilemma of social inclusion, on the one hand, and the right to not participate in play, on the other. Showing this, the article contributes to knowledge on how people age with technology; in particular, it draws attention to the limits of an ideal of transparency when social robots are included in dementia care.

Silicon caregivers: a multilevel analysis of European perspectives on robotic technologies for elderly care

ABSTRACT As populations age, women's workforce participation grows and AI advances, understanding attitudes towards care technologies becomes increasingly important. This study examines attitudes towards robot caregivers for older adults across 28 European countries, using 2017 Eurobarometer data from working-age adults (20–59; n = 13,839). We investigate how individual characteristics (gender, education, occupation) and local-level factors (GDP, female labour participation, over 65s as % of the population, spending on old age) are associated with comfort levels with domestic care robots. The results show that men, individuals with higher levels of educational attainment, and those in professional or managerial occupations report greater comfort with robot caregivers. Additionally, local context plays a significant role. Those living in local communities with higher female employment rates and lower spending on old-age support demonstrate higher acceptance of robotic care solutions. These findings highlight the dual influence of individual and community factors in shaping attitudes towards automated care technologies.

Better Apprenticeship Learning with LLM Explanations

As the population ages, care robots will play an increasing role in assisting caregiving by taking on repetitive or physically cumbersome activities. To effectively provide care, robotic agents must be able to meet the needs and preferences of care receivers. However, these needs and preferences may change over time, making it intractable to pre-define the way the care robot should act before deployment. Instead, the care robot should be able to learn directly from non-expert end-user demonstrations. However, prior work investigating the feasibility of learning a policy from older adult demonstrations finds that older adult demonstrators desire a better understanding of what the robot needs them to do, and how. To help demonstrators understand how to improve on suboptimal or heterogeneous demonstrations, we propose to utilize a Large Language Model to provide human-interpretable explanations of Shapley values of a policy. These explanations enable the demonstrator to understand how the policy is performing, and what changes are needed, informing their corrective demonstrations. We showcase our framework's performance in deterministic and stochastic versions of Wumpus World.

Framework for Integrating Large Language Models with a Robotic Health Attendant for Adaptive Task Execution in Patient Care

The development of intelligent medical service robots for patient care presents significant challenges, particularly in integrating diverse knowledge sources and enabling robots to autonomously perform tasks in dynamic and unpredictable healthcare environments. This study introduces a novel framework that combines large language models with healthcare-specific knowledge and robotic operations to enhance autonomous task execution for a Robotic Health Attendant. Utilizing OpenAI’s ChatGPT, the system processes structured information about patient care protocols and unstructured human inputs to generate context-aware robot actions. A prototype system was tested in a simulated patient room where the robot successfully performed both simple individual actions and complex tasks involving the execution of multiple actions, based on real-time dialogues with the language model and predefined task specifications. The results demonstrate the potential of language models to reduce the reliance on hardcoded logic and provide healthcare professionals with the ability to interact with robotic systems through natural language.

Digital-twin co-simulation framework to support informed decision in healthcare planning and management

This manuscript aims to show the proof-of-concept for the integration of digital twin (DT) and discrete event co-simulation through its application to forward simulation of physical activities of care providers and robots in an intensive care unit (ICU). Co-simulation focuses on modular integration of heterogeneous simulation components to capture the complexity inherent in systems. Advancing this conception, the proposed co-simulation attempted to narrow gaps with real-world systems by using DT while simultaneously leveraging the forward simulation capacity of discrete event simulation (DES). In particular, we created a co-simulation for human–robot interactions in a simulated ICU facility, which modeled the hospital layout including the facility, robot, avatars for healthcare professionals, equipment, patient bed, and vital signs, which comprise physical twin (PT). In addition, specific patient-care scenarios were defined to drive PT for which the states of interest were represented in the DT, and then used for a dynamic input to the discrete event co-simulation. At the onset of the co-simulation, the parameters needed to run DES were manually configured to align the parameters with those of the DT. For internal validation, this DES was replicated under different work-system policies, and the co-simulation outcomes were interpreted in clinical context. Our co-simulation approach has potential for application to a broader class of problems in healthcare planning and management by supporting informed decision-making. Methodologically, timely information exchanges of PT with DT, and ensuing model updates in the Discrete Event System Specification (DEVS) is a promising approach for co-simulation, to maintain robustness against perturbations to real-world systems.

Special Issue on Robotics and Mechatronics Technology for Sports, Exercise, and Health Care (Part 2)

Robotics, mechatronics, and digital technologies are advancing significantly in sports, exercise, and healthcare, and offer innovative solutions that shape the future of these fields. In Part 2 of this special issue, we examine independent research and cutting-edge developments that address new challenges and provide unique contributions to these domains. Technological advancements in assistive devices and rehabilitation offer new solutions for improving the quality of life of individuals with physical challenges. Researchers of wearable assistive devices and prosthetics continue to devise methods to enhance mobility and support physical functions, thereby benefiting both users and healthcare providers. Sports and motion analysis remains a key focus area, where innovative technologies are employed to analyze and improve athletic performance. By capturing and evaluating detailed movement data, these technologies can help athletes refine their techniques and achieve greater precision in their sports, thus ultimately resulting in enhanced performance and injury prevention. As in Part 1, the studies presented in this issue demonstrate the practical applications of cutting-edge technologies and offer insights into their future potential. We hope that these contributions will inspire researchers and practitioners alike and provide a foundation for continued advancements in these exciting and impactful fields.

Using digital technologies and applications in midwifery practice in Belgium: A descriptive cross-sectional study

IntroductionOver the past two decades, there has been a dramatic increase in the use of digital technologies within healthcare and also in midwifery. However, scarce literature exist on the use of digital technologies and applications in midwifery practice particularly in the Belgian setting. AimTo map the use of digital technologies and applications by midwives in various settings, encompassing hospitals, primary care, and educational institutions in Belgium. MethodsA descriptive cross-sectional design was used to collect data via an online questionnaire targeting at midwives working in the Flemish region, Walloon region, or Brussels-Capital region. Midwives were either Dutch-speaking or French-speaking (n = 212). The semi-structured questionnaire addressed three domains: (1) socio-demographics, (2) employment information (3) the use of digital technology, including the level of comfort with technology. Qualtrics© program was used for managing data and SPSS v28.0© for data analysis using descriptive statistics, Chi² analysis, and independent sample t-test. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines. ResultsAmong respondents, 58% reported the use of digital technologies and applications, with electronic health records (89.6%), electronic prescriptions (65.6%), and remote patient monitoring (51.2%) commonly utilized. Sensor technology (7.2%), mixed care (3.8%), care robots (2.5%), and wearable devices (1.9%) were very rarely used. The target groups for these digital technologies and applications generally encompass all stages of the perinatal period. Midwives felt overall highly confident with these technologies. Younger participants and those with a Master's or PhD degree exhibited greater comfort scores in digital technology use. No significant relationships were observed between socio-demographic characteristics and the adoption of digital technology. ConclusionThe results highlight the potential for incorporating digital technologies and applications into various midwifery care settings. Addressing barriers and enhancing usability can optimize technology integration, contributing to personalized high-quality care, ultimately improving perinatal health outcomes.

HoLLiECares - Development of a multi-functional robot for professional care.

Germany's healthcare sector suffers from a shortage of nursing staff, and robotic solutions are being explored as a means to provide quality care. While many robotic systems have already been established in various medical fields (e.g., surgical robots, logistics robots), there are only a few very specialized robotic applications in the care sector. In this work, a multi-functional robot is applied in a hospital, capable of performing activities in the areas of transport and logistics, interactive assistance, and documentation. The service robot platform HoLLiE was further developed, with a focus on implementing innovative solutions for handling non-rigid objects, motion planning for non-holonomic motions with a wheelchair, accompanying and providing haptic support to patients, optical recognition and control of movement exercises, and automated speech recognition. Furthermore, the potential of a robot platform in a nursing context was evaluated by field tests in two hospitals. The results show that a robot can take over or support certain tasks. However, it was noted that robotic tasks should be carefully selected, as robots are not able to provide empathy and affection that are often required in nursing. The remaining challenges still exist in the implementation and interaction of multi-functional capabilities, ensuring ease of use for a complex robotic system, grasping highly heterogeneous objects, and fulfilling formal and infrastructural requirements in healthcare (e.g., safety, security, and data protection).

Human-Robot Interaction and Social Robot: The Emerging Field of Healthcare Robotics and Current and Future Perspectives for Spinal Care.

Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists.

Care robot literacy: integrating AI ethics and technological literacy in contemporary healthcare

AbstractHealthcare work is guided by care ethics, and any technological changes, including the use of robots and artificial intelligence (AI), must comply with existing norms, values and work practices. By bridging technological literacy and AI ethics, this study provides a nuanced definition and an integrative conceptualization of care robot literacy (CRL) for contemporary care work. Robotized care tasks require new orientation and qualifications on the part of employees. CRL is considered as one of these new demands, which requires practitioners to have the resources, skills and understanding necessary to work with robots. This study builds on sociotechnical approach of literacy by highlighting a dynamic relationship of care robotization in which successful human–technology interaction relies on exchanges between the technological and the social. Our findings from directed content analysis and theoretical synthesis of in-demand technological literacy and AI ethics in care work emphasize competencies and situational awareness regarding both using the robot and communicating about the care robot. The initial conceptualization of CRL provides a conceptual framework for future studies, implementation and product development of care robots, drastically differing from studying, implementing and developing robots in general. In searching for technologically sound and ethically compliant solutions, the study advocates for the future significance of context-specific CRL as valuable addition to the terminology of ethical AI in healthcare.

Nursing Staff's Perspectives of Care Robots for Assisted Living Facilities: Systematic Literature Review.

Care robots have been proposed in response to nursing shortages in assisted living facilities (ALFs) and the growing population of older adults. While the use of care robots may improve the general health and well-being of older adults, their introduction changes the work of nursing staff fundamentally, and it has implications for the entire health care system. In developing such technology, it is important to include end users, but so far, the nursing staff's perspectives have largely been ignored. This study aims to examine the literature on nursing staff's attitudes, needs, and preferences related to the use of care robots in ALFs, in order to discover gaps in the literature and guide future research. This review follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 protocol. On May 12, 2023, we searched PubMed, CINAHL Plus with Full Text, PsycINFO, the IEEE Xplore Digital Library, and the ACM Digital Library using predetermined search terms. Included publications, written in English, focused on the predevelopment phase, in which information was gathered on nursing staff's attitudes, needs, and preferences regarding care robots for ALFs. Publications were excluded if they did not provide peer-reviewed empirical data. The studies' findings were summarized, coded, and analyzed into major themes using thematic analysis and narrative synthesis. Their quality was assessed using McGill University's Mixed Methods Appraisal Tool and the Joanna Briggs Institute's critical appraisal tools. The final sample included 15 studies. Most of the studies (n=11, 73%) were rated as good quality; however, there was a general lack of reporting on important methodological decisions and sample characteristics. Nursing staff desired care robots that could assist with physically demanding tasks and reduce their workload but had mixed feelings on whether robots could or should assist with social tasks. In addition, nursing staff are concerned about the ethics of care robots, as well as about their safety, accessibility, and operability. The nursing staff's culture, qualification, and role in the facility may influence their perspectives of care robots. The studies lacked theory-driven designs and large sample sizes. Eight (53%) studies mentioned using a participatory design approach, but a lack of established criteria for what constitutes participatory design leads to varying degrees of methodological quality. There was consensus among nursing staff that care robots should serve as nursing assistants to reduce workload. Whether robots could or should assist with social tasks remains a question. Further research is needed to mitigate nursing staff's concerns and understand the socioecological factors that influence their perspectives of care robots and their adoption in ALFs. In addition, theory-driven and large sample size study designs are necessary, as well as work to develop clear criteria for related participatory design research.

Perceived Usefulness of Robotic Technology for Patient Fall Prevention.

Technology has the potential to prevent patient falls in healthcare settings and to reduce work-related injuries among healthcare providers. However, the usefulness and acceptability of each technology requires careful evaluation. Framed by the Technology Acceptance Model (TAM) and using the Adaptive Robotic Nursing Assistant (ARNA) to assist with patient ambulation, the present study examined the perceived usefulness of robots in patients' fall prevention with implications for preventing associated work-related injuries among healthcare providers. Employing an experimental design, subjects were undergraduate nursing students (N = 38) and one external subject (not a nursing student) who played the role of the patient. Procedures included subjects ambulating a simulated patient in three ways: (a) following the practice of a nurse assisting a patient to walk with the patient wearing a gait belt; (b) an ARNA-assisted process with the gait belt attached to ARNA; (c) an ARNA-assisted process with a subject walking a patient wearing a harness that is attached to ARNA. Block randomization was used with the following experimental scenarios: Gait Belt (human with a gait belt), "ARNA + Gait Belt" (a robot with a gait belt), and "ARNA + Harness" (a robot with a harness). Descriptive statistics and a multiple regression model were used to analyze the data and compare the outcome described as the Perceived Usefulness (PU) of a robot for patient walking versus a human "nurse assistant" without a robot. The independent variables included the experimental conditions of "Gait Belt," "ARNA + Gait Belt," and "ARNA + Harness," the subject's age, race, and previous videogame playing experience. Results indicated that PU was significantly higher in the Gait Belt + ARNA and Harness + ARNA conditions than in the Gait Belt condition (p-value <.01 for both variables). In examining potential influencing factors, the effects of race (White, African American, and Asian), age, and previous video-playing experience were not statistically significant (p-value >.05). Results demonstrated that using robot technology to assist in walking patients was perceived by subjects as more useful in preventing falls than the gait belt. Patient fall prevention also has implications for preventing associated work-related injuries among healthcare providers. Understanding the effects of a subject's perceptions can guide further development of assistive robots in patient care. Robotic engineers and interdisciplinary teams can design robots to accommodate worker characteristics and individual differences to improve worker safety and reduce work injuries.

Digital Technology in Healthcare—An Ethical Overview

This overview of ethical aspects of artificial intelligence (AI) in healthcare is organized according to major types of medical activities. It discusses important ethical problems in (1) diagnostic uses of AI such as image interpretation and text interpretation, (2) the use of AI as decision support or even as decision-maker, (3) its use for treatment, for instance in robotic surgery, exoskeletons, virtual psychotherapy and therapeutic robots (care robots), and (4) the use of AI for healthcare documentation and communication. Summing up, we emphasize two major challenges in the introduction of AI that should concern not only healthcare professionals but also higher level decision-makers such as politicians and hospital directors. The first of these is the need to retain human contacts between patients and healthcare, in particular contacts that are conducive to patient health and well-being. The second is the need to ensure that the introduction of AI in healthcare does not create or exacerbate injustices in healthcare. This can happen if prevalent human biases are encoded in AI tools. It can also occur if people with less money have to use inexpensive AI tools such as virtual psychotherapists whereas the well-to-do have access to a human psychotherapist. On the other hand, AI tools can be used to provide better healthcare to all who need it, and they can also be programmed to avoid biases and other mistakes that humans are prone to. The article concludes with brief summaries of the articles in the special issue on AI in healthcare that it introduces.

Can an AI-carebot be filial? Reflections from Confucian ethics.

This article discusses the application of artificially intelligent robots within eldercare and explores a series of ethical considerations, including the challenges that AI (Artificial Intelligence) technology poses to traditional Chinese Confucian filial piety. From the perspective of Confucian ethics, the paper argues that robots cannot adequately fulfill duties of care. Due to their detachment from personal relationships and interactions, the "emotions" of AI robots are merely performative reactions in different situations, rather than actual emotional abilities. No matter how "humanized" robots become, it is difficult to establish genuine empathy and a meaningful relationship with them for this reason. Even so, we acknowledge that AI robots are a significant tool in managing the demands of elder care and the growth of care poverty, and as such, we attempt to outline some parameters within which care robotics could be acceptable within a Confucian ethical system. Finally, the paper discusses the social impact and ethical considerations brought on by the interaction between humans and machines. It is observed that the relationship between humans and technology has always had both utopian and dystopian aspects, and robotic elder care is no exception. AI caregiver robots will likely become a part of elder care, and the transformation of these robots from "service providers" to "companions" seems inevitable. In light of this, the application of AI-augmented robotic elder care will also eventually change our understanding of interpersonal relationships and traditional requirements of filial piety.

Special Issue on Robotics and Mechatronics Technology for Sports, Exercise, and Health Care (Part 1)

Robotics, mechatronics, and digital technologies are rapidly advancing in the fields of sports, exercise, and healthcare, and their applications are expanding daily. In part 1 of our special issue, we focus on the innovative contributions of cutting-edge technologies in various domains. Robotics technology is crucial in sports and exercise training as it monitors individual movements and forms, provides user feedback, and enables effective training. The development of robots to enhance the accuracy and reproducibility of sports techniques is a key element directly linked to performance improvements. Robotics and mechatronics provide new possibilities for treatment and rehabilitation in healthcare. Developing beneficial systems for medical professionals and patients contributes to increased precision in surgery and productive support in rehabilitation. Power assistance and motion augmentation are witnessing advancements that prolong individual capabilities and achieve better performance. These studies may reduce the physical burden of daily activities and specific tasks, thereby enhancing efficiency. Therefore, studies on haptics and sensory feedback are important. Efforts to improve user interfaces through virtual haptic experiences represent a promising new application of digital technology. The studies included in part 1 of this special issue present recent technological trends and practical examples of sports, exercise, and healthcare and aim to provide valuable information and inspire the readers. We hope that these studies will serve as significant steps toward future technological advancement and social implementation.

Co-creating Humanistic AI AgeTech to Support Dynamic Care Ecosystems: A Preliminary Guiding Model.

As society rapidly digitizes, successful aging necessitates using technology for health and social care and social engagement. Technologies aimed to support older adults (e.g., smart homes, assistive robots, wheelchairs) are increasingly applying artificial intelligence (AI), and thereby creating ethical challenges to technology development and use. The international debate on AI ethics focuses on implications to society (e.g., bias, equity) and to individuals (e.g., privacy, consent). The relational nature of care, however, warrants a humanistic lens to examine how "AI AgeTech" will shape, and be shaped by, social networks or care ecosystems in terms of their care actors (i.e., older adults, care partners, service providers); inter-actor relations (e.g., care decision-making) and relationships (e.g., social, professional); and evolving care arrangements. For instance, if an older adult's reduced functioning leads actors to renegotiate their risk tolerances and care routines, smart homes or robots become more than tools that actors configure; they become semi-autonomous actors, in themselves, with the potential to influence functioning and interpersonal relationships. As an experientially-diverse, transdisciplinary working group of older adults, care partners, researchers, clinicians, and entrepreneurs, we co-constructed intersectional care experiences, to guide technology research, development, and use. Our synthesis contributes a preliminary guiding model for AI AgeTech innovation that delineates humanistic attributes, values, and design orientations, and captures the ethical, sociological, and technological nuances of dynamic care ecosystems. Our visual probes and recommended tools and techniques offer researchers, developers/innovators, and care actors concrete ways of using this model to promote successful aging in AI-enabled futures.

Telepresence robots in mental health care to enable digital participation: A qualitative exploratory pilot study

Telepresence robots in mental health care to enable digital participation: A qualitative exploratory pilot study

Ethical challenges in integrating social robots in geriatric care: Development and assessment of an educational module for health and social care professionals

Ethical challenges in integrating social robots in geriatric care: Development and assessment of an educational module for health and social care professionals

The impact of utilizing care robots on sustainability

The impact of utilizing care robots on sustainability

Public perceptions of care robots

Public perceptions of care robots