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Examples of healthcare robots. Top: Paro (credited to AIST, Japan). Middle: Movaid (reprinted from Technology and Disability, 10, Dario P., Guglielmelli E., Laschi C., Teti G. MOVAID: a personal robot in everyday life of disabled and elderly people, 77-93, Copyright (1999), with permission from IOS Press). Bottom: Hopis (reproduced with permission of LinuxInsider.com and ECT News Network. Copyright 2003-2009 ECT News Network, Inc. All rights reserved)
Source publication
The rapidly ageing population is placing increasing strain on healthcare services. Robots have been proposed as a way to assist
people to stay healthy and safe in their own homes. However, despite the need for such assistive devices and the success of
some healthcare robots, other robots have had a poor response. This article reviews the literature...
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Background:
Artificial intelligence (AI) is the term used to describe the use of computers and technology to simulate intelligent behavior and critical thinking comparable to a human being. John McCarthy first described the term AI in 1956 as the science and engineering of making intelligent machines.
Objective:
This descriptive article gives a...
Citations
... Beyond these practical examples, the broader research landscape con rms that nurses' acceptance of assistive robots is in uenced and moderated by a variety of factors [28,[36][37][38][39]. These can be broadly categorized into individual, technological, and organizational factors [36]. ...
... These include age, gender, education, and the professional and cultural background [37,41,42,[44][45][46]. ...
... Regarding the inherent characteristics of a robotic system, it was found that their acceptance also depends on their shape, functions, and capabilities [41]. The results indicate that to increase the likelihood of acceptance a robot should operate safely and reliably at a slow pace, be compact, easy to use, and have a serious appearance and demeanor while avoiding overly human-like features [37]. ...
Background: Nursing is increasingly being enhanced by the use of assistive technologies. These technological advances include assistive robots, which have already shown positive impacts on older adults as well as formal and informal caregivers. However, a lack of end-user acceptance is considered one of the most significant barriers to the implementation and successful long-term use of robots in nursing. Therefore, a user-centered research and development approach is particularly important to ensure the use of robotics is not technology-driven, but oriented towards nursing goals and processes.
Methods: Our study presents the results of the evaluation of a service robot developed for routine tasks in inpatient care in a user-centered design. In three scenarios (information service, delivery of items, and delivery of beverages), 30 nurses tested the robot in a simulated care setting with regard to acceptance-related dimensions and the intention to use the system. In addition, the participants’ general attitudes towards robots and robotics experiences were surveyed.
Results: Generally, the robot was seen as user-friendly and useful. Skepticism towards the system was low and the accessibility was rated as moderate. Overall, a high intention to use was reported. No significant differences were identified in the assessment of the robot between participants with and without robotics experience. However, dependency analyses showed various strongly significant correlations. Usability, perceived usefulness, and accessibility as well as a personal positive attitude towards robots all correlated positively with the intention to use. Skepticism towards the system correlated negatively.
Conclusion: In our study, a high level of acceptance was measured for the developed service robot within the selected application scenarios. In line with the current state of research, our results suggest that the target group-specific communication of robot capabilities and limitations as well as opportunities for personal experience are particularly important aspects for promoting the intention to use and acceptance of robotic systems. Strategies for the transfer of knowledge and skills as well as financing concepts are urgently needed so that the nursing sector can become more widely aware of and benefit from the potential of robotics.
... (Broadbent et al., 2009;Deutsch et al., 2019). ...
In the context of interactions between humans and robots at work, this research examines the dynamics of obedience and power. We replicated and extended the previous studies by comparing the responses of participants to a humanoid robot, which acts as an authoritative figure, against those to a human in a similar role. While the humanoid robot commanded a significant level of obedience (63%), it was notably lower than that for its human counterpart (75%). Moreover, work under the robot's supervision was performed more slowly and less effectively. The results give a good insight into the practical implications of using humanoid robots in official roles, especially for repeated and tedious tasks or challenging work activities.
... Assistive Robotics-Designed to help users with daily tasks and enable them to live independently [17]. ...
This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within smart environments. We explore the integration of smart environments with sensor technologies, digital health capabilities, and location-based services, focusing on their impacts on healthcare objectives and outcomes. This work analyzes the foundational technologies, encompassing the Internet of Things (IoT), Internet of Medical Things (IoMT), machine learning (ML, and artificial intelligence (AI), that underpin the functionalities within smart environments. We also examine the unique characteristics of smart homes and smart hospitals, highlighting their potential to revolutionize healthcare delivery through remote patient monitoring, telemedicine, and real-time data sharing. The review presents a novel solution framework leveraging sensor-driven digital twins to address both healthcare needs and user requirements. This framework incorporates wearable health devices, AI-driven health analytics, and a proof-of-concept digital twin application. Furthermore, we explore the role of location-based services (LBS) in smart environments, emphasizing their potential to enhance personalized healthcare interventions and emergency response capabilities. By analyzing the technical advancements in sensor technologies and digital twin applications, this review contributes valuable insights to the evolving landscape of smart environments for healthcare. We identify the opportunities and challenges associated with this emerging field and highlight the need for further research to fully realize its potential to improve healthcare delivery and patient well-being.
... The recent revolutionization of AI with assistive robots has transformative potential for eldercare, providing a new paradigm in how to approach management as people age (Lajante et al., 2023;Cavallo et al., 2018). Equipped with advanced sensors and machine learning algorithms, these robots can help the elderly with everyday chores, monitor health parameters, reduce the burden on human caregivers, and potentially delay the need for institutionalized care (Broadbent et al., 2009) because they can provide numerous different types of support including social interaction, thus improving quality of life and independence (Turja et al., 2020;Kachouie et al., 2014). Furthermore, these robots will alleviate the burden on the healthcare systems by meeting the increasing demand for human care providers that will eventually exceed the capacity of human personnel to serve an aging society (Lajante et al., 2023;Broekens et al., 2009). ...
Purpose
The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.
Design/methodology/approach
Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.
Findings
Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.
Practical implications
Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.
Originality/value
Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.
... For addressing BPSDs in the early stages, non-pharmacological interventions that do not involve medication are recommended because of concerns about the side effects of pharmacological approaches [3]. Recently, robot therapy has started to use communication robots such as animal-like robots and interactive robots, and its effectiveness is being scientifically investigated [4]. ...
... In this way, they would have more time left for other, even more important job related tasks. These expectations are in line with other research discussing the potential of robots, in which is often argued that they may be able to reduce burden of care [16,[30][31][32][33][34]. ...
In the context of recent demographic changes and related societal challenges, socially assistive robots (SARs) are considered having the potential to support independence and care of older adults. However, little is known about the preferred SAR-features of older adults with mild cognitive impairment (MCI) residing in assisted living and their caregivers. Semi-structured interviews were conducted with two stakeholder groups: older adults with MCI and their (in)formal caregivers. Inductive thematic analysis was used to analyse the data. Forty individual semi-structured interviews were conducted with older adults with MCI (N = 30) and (in)formal caregivers (N = 10). Data revealed seven common role-expectations regarding SARs for both the older adults and caregivers: (1) companion, (2) health assistant, (3) household assistant, (4) physical assistant, (5) cognitive assistant, (6) coach, (7) leisure buddy. One additional, eighth role was identified for the caregivers, i.e. job assistant. The results of this study provide a better knowledge of the features to consider during the development process of SARs in order to maximize the perceived usefulness and hence the intention to use and actual adoption. Additionally, a feasibility analysis showed which features should have the primary focus during the further software development of an existing SAR called James® within the ReMIND-project.
... This evolution has prompted research on cobotics that focused on manufacturing and military settings and on efficiency goals (Moulières-Seban et al., 2016). Such efficiency considerations are relevant to healthcare as well (Broadbent et al., 2009). For example, radiology reviews that rely on artificial intelligence (AI) can be completed 62%-97% faster (Kalis et al., 2018). ...
In cobotic service teams, employees and robots collaborate to serve customers. As cobotic teams become more prevalent, a key question arises: How do consumers respond to cobotic teams, as a function of the roles shared by employees and robots (robots in superordinate roles as team leaders and humans in subordinate roles as assistants, or vice versa)? Six studies, conducted in different healthcare settings, show that consumers respond less favorably to robot-led (vs. human-led) teams. In delineating the process underlying these responses, the authors demonstrate that consumers ascribe less power to robot (vs. human) team leaders, which increases consumer anxiety and drives downstream responses through serial mediation. Further examining the power dynamics in cobotic service encounters, the authors identify boundary conditions that help mitigate negative consumer responses (increasing consumers’ power by letting them choose the robot in the service team, leveraging consumers’ power distance beliefs, and reinforcing the robot’s performance capabilities).
... Recently, there have been notable developments in the field of robotics and artificial intelligence which have facilitated the emergence of new solutions to meet the needs of people with specific requirements [33][34][35] in a context where the aging population is creating an increasing demand for health services. ...
In the face of today’s ever-evolving global health landscape and ambient assisted living (AAL), marked by the persistent emergence of novel viruses and diseases that impact vulnerable categories and individual safety, the need for innovative disinfection solutions has surged to unprecedented levels. In pursuit of advancing the field of autonomous UV-C disinfection robotics, we conducted two comprehensive state-of-the-art analyses: the first one in the literature and the second one in existing commercial disinfection robots to identify current challenges. Of all of the challenges, we consider the most outstanding ones to be safeguarding humans and animals and understanding the surroundings while operating the disinfection process challenges that we will address in this article. While UV-C lamps have demonstrated their effectiveness in sterilizing air and surfaces, the field of autonomous UV-C disinfection robotics represents a critical domain that requires advancement, particularly in safeguarding the wellbeing of humans and animals during operation. Operating UV-C disinfection robots in close proximity to humans or animals introduces inherent risks, and existing disinfection robots often fall short in incorporating advanced safety systems. In response to these challenges, we propose the RoboCoV Cleaner—an indoor autonomous UV-C disinfection robot equipped with an advanced dual and redundant safety system. This novel approach incorporates multiple passive infrared (PIR) sensors and AI object detection on a 360-degree camera. Under our test, the dual-redundant system reached more than 90% when detecting humans with high accuracy using the AI system 99% up to 30 m away in a university hallway (different light conditions) combined with the PIR system (with lower accuracy). The PIR system was proved to be a redundant system for uninterrupted operation during communication challenges, ensuring continuous sensor information collection with a swift response time of 50 ms (image processing within 200 ms). It empowers the robot to detect and react to human presence, even under challenging conditions, such as when individuals wear masks, in complete darkness, under UV light, or in environments with blurred visual conditions. In our test, the detection system performed outstandingly well with up to 99% detection rate of humans. Beyond safety features, the RoboCoV Cleaner can identify objects in its surroundings. This capability empowers the robot to discern objects affected by UV-C light, enabling it to apply specialized rules for targeted disinfection. The proposed system exhibits a wide range of capabilities beyond its core purpose of disinfection, making it suitable for healthcare facilities, universities, conference venues, and hospitals. Its implementation has the ability to improve significantly human safety and protect people. By showcasing the RoboCoV Cleaner’s safety-first approach and adaptability, we aim to set a new benchmark for UV-C disinfection robots, promoting clean and secure environments while protecting vulnerable people, even in challenging scenarios.
... Non-humanoid robots, like the quadruped robot that is the focus of this study, have a wider range of functionality as they can interact with the environment, such as task assistance/completion for PwADRD (Morris et al. 2022). Furthermore, prior studies have focused on the perception of PwADRD regarding robotics (Broadbent et al. 2009, Smarr at al. 2014, Søraa et al. 2023, Pino et al. 2015, but fail to assess how those around PwADRD (caregivers, loved ones, etc.) perceive them. This study bridges that gap by surveying all those affected by dementia. ...
... Even worse, according to Q1 in the third section of the survey with an average score of 1.68/5, very few respondents are familiar with the concept of robots being used for dementia care. These results are similar to those found in other studies that focus on PwADRD perception of robots in healthcare (Broadbent et al. 2009, Smarr et al. 2014, Søraa et al. 2023, Pino et al. 2015. This point shows that researchers must do a better job of informing the public of their research and its impact on the healthcare world. ...
The rapid increase in the number of persons with Alzheimer’s Disease or related dementia has led many researchers to develop supplemental care to assist caregivers. One such form of care comes in the form of a quadruped robot that can interact with its environment to provide additional care. However, before such technology is fully implemented, researchers must understand how aware the public is of such technology for dementia care and how they perceive it. In this study, we surveyed 16 adults, all but one of which have been affected by dementia either directly or indirectly. We asked them questions regarding their attitude towards technology in healthcare and the quadruped robot that was demoed for them. It was found that people positively accept these robotic forms of dementia care, even if they do not have a comprehensive understanding of them. Furthermore, regarding the quadruped robot, people do perceive it positively but are not as confident in its ability to provide adequate care. They also have reservations about using robots to care for persons with dementia, mostly because of the lack of a “human touch,” and are afraid that robots might replace human caregivers altogether. From these results, researchers must do their best to not only develop the technology to be as robust as possible but keep the public informed of their research to bridge the gap between this revolutionary technology and its end users.
... The 2020 Census underscores this shift, revealing that one in six Americans now belongs to this age group [7]. Accompanying this change in age demographics is a rise in chronic health issues, necessitating an expanded range of healthcare services [3,6,13]. ...
... Research in this field has been extensive, focusing on identifying the factors that influence acceptance [9,11,14,20]. This includes aspects of robot aesthetic design features such as appearance [2,15], and functionalities like mobility assistance [3,6,10,13,27]. However, there remains a gap in understanding which features are most critical in gaining acceptance among older adults, leaving developers without specific guidance on feature prioritization. ...
... We focused on how different features, from functional ones providing assistance to characteristics enhancing human-robot interactions, influence user acceptance. The outcome of this extensive review is the identification of 27 distinct features pertinent to healthcare robots for older adults [3,6,13,21,27,35]. These features are detailed in Table 2. 2.2.2 Questionnaire design. ...
Healthcare robots at home are increasingly essential for promoting the independence of older adults, yet their widespread acceptance is hindered by a lack of clarity regarding optimal design features. To address this, this study employs the Kano model to systematically identify and prioritize the features of healthcare robots that most significantly influence user satisfaction and acceptance among older adults. We conducted a survey study with 253 U.S. older adults to evaluate a variety of robot features. The results highlight design features that markedly affect user satisfaction and acceptance. 'Medication Management' and 'Managing Illness and Monitoring Health' are identified as one-dimensional features, whereas 'Animal-like Appearance' is a less favored reverse feature, potentially diminishing satisfaction. 'Housework' along with seven other features, is recognized as attractive, with sixteen features deemed indifferent.
