Socially Assistive Robots Research Articles

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.

Socially Assistive Robots’ Deployment in Healthcare Settings: A Global Perspective

One of the major areas where social robots are finding their place in society is for healthcare-related applications. Yet, very little research has mapped the deployment of socially assistive robots (SARs) in real settings. By using a documentary research method, we traced back 279 experiences of SARs deployments in hospitals, elderly care centers, occupational health centers, private homes, and educational institutions worldwide that involved 52 different robot models. We retrieved, analyzed, and classified the functions that SARs develop in these experiences, the areas in which they are deployed, the principal manufacturers, and the robot models that are being adopted. The functions we identified for SARs are entertainment, companionship, telepresence, edutainment, providing general and personalized information or advice, monitoring, promotion of physical exercise and rehabilitation, testing and pre-diagnosis, delivering supplies, patient registration, giving location indications, patient simulator, protective measure enforcement, medication and well-being adherence, translating and having conversations in multiple languages, psychological therapy, patrolling, interacting with digital devices, and disinfection. Our work provides an in-depth picture of the current state of the art of SARs’ deployment in real scenarios for healthcare-related applications and contributes to understanding better the role of these machines in the healthcare sector.

Exploring the needs of children and caregivers to inform design of an artificial intelligence-enhanced social robot in the pediatric emergency department.

Socially assistive robots (SARs) are a promising tool to manage children's pain and distress related to medical procedures, but current options lack autonomous adaptability. The aim of this study was to understand children's and caregivers' perceptions surrounding the use of an artificial intelligence (AI)-enhanced SAR to provide personalized procedural support to children during intravenous insertion (IVI) to inform the design of such a system following a user-centric approach. This study presents a descriptive qualitative needs assessment of children and caregivers. Data were collected via semi-structured individual interviews and focus groups. Participants were recruited from two Canadian pediatric emergency departments (EDs) between April 2021 and January 2022. Eleven caregivers and 19 children completed 27 individual interviews and one focus group. Three main themes were identified: A. Experience in the clinical setting, B. Acceptance of and concerns surrounding SARs, and C. Features that support child engagement with SARs. Most participants expressed comfort with robot technology, however, concerns were raised about sharing personal information, photographing/videotaping, and the possibility of technical failure. Suggestions for feature enhancements included increasing movement to engage a child's attention and tailoring language to developmental age. To enhance the overall ED experience, participants also identified a role for the SAR in the waiting room. Artificial intelligence-enhanced SARs were perceived by children and caregivers as a promising tool for distraction during IVIs and to enhance the overall ED experience. Insights collected will be used to inform the design of an AI-enhanced SAR.

Older People’s Perspectives on Privacy, Surveillance and Consumer Socially Assistive Robots: Paradoxes, Trade-offs and the Future of Privacy Protection

Older People’s Perspectives on Privacy, Surveillance and Consumer Socially Assistive Robots: Paradoxes, Trade-offs and the Future of Privacy Protection

SoftSAR: The New Softer Side of Socially Assistive Robots-Soft Robotics with Social Human-Robot Interaction Skills.

When we think of "soft" in terms of socially assistive robots (SARs), it is mainly in reference to the soft outer shells of these robots, ranging from robotic teddy bears to furry robot pets. However, soft robotics is a promising field that has not yet been leveraged by SAR design. Soft robotics is the incorporation of smart materials to achieve biomimetic motions, active deformations, and responsive sensing. By utilizing these distinctive characteristics, a new type of SAR can be developed that has the potential to be safer to interact with, more flexible, and uniquely uses novel interaction modes (colors/shapes) to engage in a heighted human-robot interaction. In this perspective article, we coin this new collaborative research area as SoftSAR. We provide extensive discussions on just how soft robotics can be utilized to positively impact SARs, from their actuation mechanisms to the sensory designs, and how valuable they will be in informing future SAR design and applications. With extensive discussions on the fundamental mechanisms of soft robotic technologies, we outline a number of key SAR research areas that can benefit from using unique soft robotic mechanisms, which will result in the creation of the new field of SoftSAR.

Seeking at-home long-term autonomy of assistive mobile robots through the integration with an IoT-based monitoring system

In this paper, we propose a system that stems from the integration of an autonomous mobile robot with an IoT-based monitoring system to provide monitoring, assistance, and stimulation to older adults living alone in their own houses. The creation of an Internet of Robotics Things (IoRT) based on the interplay between pervasive smart objects and autonomous robotic systems is claimed to enable the creation of innovative services conceived for assisting the final user, especially in elderly care. The synergy between IoT and a Socially Assistive Robot (SAR) was conceived to offer robustness, reconfiguration, heterogeneity, and scalability, by bringing a strong added value to both the current SAR and IoT technologies. First, we propose a method to achieve the synergy and integration between the IoT system and the robot; then, we show how our method increases the performance and effectiveness of both to provide long-term support to the older adults. To do so, we present a case-study, where we focus on the detection of signs of the frailty syndrome, a set of vulnerabilities typically conveyed by a cognitive and physical decline in older people that concur in amplifying the risks of major diseases hindering the capabilities of independent living. Experimental evaluation is performed in both controlled settings and in a long-term real-world pilot study with 9 older adults in their own apartments, where the system was deployed autonomously for, on average, 12 weeks.

RESEARCH AT THE INTERSECTION OF TECHNOLOGY AND AGING

Abstract New and emerging technologies offer opportunities for the delivery of wide-ranging, adaptable interventions to improve quality of life of older adults. Novel technologies can also improve the quality of measurement methods used in aging research. In this symposium five presentations will describe advanced technologies to promote health and function in older adults. The first will discuss the Urban Aging Residents Coalition (UARC), an organization founded in partnership with an African American older adult community leader to address engaging urban older adults with technology. A primary goal of UARC is to prevent social isolation and promote mental wellness through education and computer literacy. The second presentation will describe a project testing socially assistive robots (SARs) to complement personnel resources in older adults with cognitive impairment in long term care facilities. Study participants were successfully engaged in a participatory design involving repeated sessions with SARs that resulted in prototype refinement. The third presentation will describe current applications of patient communication technologies in acute-critical care settings with a focus on the user experience among older adult patients. The fourth will report on the implementation of an ongoing, in-home Smarthealth technology intervention for two older adult family caregivers of persons with dementia. Study findings showed the intervention improved self-awareness of emotional care and reactions to care recipients. The final presentation will explain an advanced wound measurement system using artificial intelligence to track healing progress in clinical research. The presentations will highlight technologies to support healthy aging and discuss implication for practice, policy, and research.

CLARA: Building a Socially Assistive Robot to Interact with Elderly People

Although the global population is aging, the proportion of potential caregivers is not keeping pace. It is necessary for society to adapt to this demographic change, and new technologies are a powerful resource for achieving this. New tools and devices can help to ease independent living and alleviate the workload of caregivers. Among them, socially assistive robots (SARs), which assist people with social interactions, are an interesting tool for caregivers thanks to their proactivity, autonomy, interaction capabilities, and adaptability. This article describes the different design and implementation phases of a SAR, the CLARA robot, both from a physical and software point of view, from 2016 to 2022. During this period, the design methodology evolved from traditional approaches based on technical feasibility to user-centered co-creative processes. The cognitive architecture of the robot, CORTEX, keeps its core idea of using an inner representation of the world to enable inter-procedural dialogue between perceptual, reactive, and deliberative modules. However, CORTEX also evolved by incorporating components that use non-functional properties to maximize efficiency through adaptability. The robot has been employed in several projects for different uses in hospitals and retirement homes. This paper describes the main outcomes of the functional and user experience evaluations of these experiments.

Between fear and trust: Older adults’ evaluation of socially assistive robots

Socially Assistive Robots (SARs) are expected to support autonomy, aging in place, and wellbeing in later life. Acceptance and successful assimilation of SARs among older adults depend ontheir Quality Evaluations (QEs), namely, the pragmatic and hedonic evaluations and overall attractiveness. Previous studies showed that trust in robots significantly enhances QE, while technophobia considerably decreases it. However, so far, these key factors have always been explored separately. Applying a case study approach, the current research aimed to examine the relative impact of these two factors on older persons’ QE of SARs. The study was based on an online survey of 384 individuals aged 65 and above. Respondents were presented with a video of Gymmy, a robotic system for physical and cognitive training, and filled out a questionnaire relating to that system. The results indicated a positive association between trust and QE and a negative association between technophobia and QE. A simultaneous exploration demonstrated that the relative impact of technophobia was significantly more substantial than that of trust. In addition, the pragmatic qualities of the robot were found to be more crucial to its QE than the social aspects of use. The findings suggest that implementing robotics technology in later life strongly depends on reducing older adults’ technophobia regarding the convenience of using SARs. The study also highlights the importance of simultaneous explorations of facilitators and inhibitors to SARs use.

Conversational Affective Social Robots for Ageing and Dementia Support

Socially assistive robots (SAR) hold significant potential to assist older adults and people with dementia in human engagement and clinical contexts by supporting mental health and independence at home. While SAR research has recently experienced prolific growth, long-term trust, clinical translation, and patient benefit remain immature. Affective human–robot interactions are unresolved and the deployment of robots with conversational abilities is fundamental for robustness and human–robot engagement. In this article, we review the state of the art within the past two decades, design trends, and current applications of conversational affective SAR for ageing and dementia support. A horizon scanning of AI voice technology for healthcare, including ubiquitous smart speakers, is further introduced to address current gaps inhibiting home use. We discuss the role of user-centered approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarize the state of development in interactions using speech and natural language processing, which forms a baseline for longitudinal health monitoring and cognitive assessment. Drawing from this foundation, we identify open challenges and propose future directions to advance conversational affective social robots for: 1) user engagement; 2) deployment in real-world settings; and 3) clinical translation.

A Review on Usability and User Experience of Assistive Social Robots for Older Persons

In the advancement of human-robot interaction technology, assistive social robots have been recognized as one of potential technologies that can provide physical and cognitive supports in older person’s care. However, a major challenge faced by the designers is to develop an assistive social robot with prodigious usability and user experience for older persons who were known to have physical and cognitive limitations. A considerable number of published literatures was reporting on the technological design process of assistive social robots. However, only a small amount of attention has been paid to review the usability and user experience of the robots. The objective of this paper is to provide an overview of established researches in the literatures concerning usability and user experience issues faced by the older persons when interacting with assistive social robots. The authors searched relevant articles from the academic databases such as Google Scholar, Scopus and Web of Science as well as Google search engine for the publication period 2000 to 2021. Several search keywords were typed such as ‘older persons’ ‘elderly’, ‘senior citizens’, ‘assistive social robots’, ‘companion robots’, ‘personal robots’, ‘usability’ and ‘user experience’. This online search found a total of 215 articles which are related to assistive social robots in elderly care. Out of which, 54 articles identified as significant references, and they were examined thoroughly to prepare the main content of this paper. This paper reveals usability issues of 28 assistive social robots, and user experience feedback based on 41 units of assistive social robots. Based on the research articles scrutinized, the authors concluded that the key elements in the design and development of assistive social robots to improve acceptance of older persons were determined by three factors: functionality, usability and users’ experience. Functionality refers to ability of robots to serve the older persons. Usability is ease of use of the robots. It is an indicator on how successful of interaction between the robots and the users. To improve usability, robot designers should consider the limitations of older persons such as vision, hearing, and cognition capabilities when interactingwith the robots. User experience reflects to perceptions, preferences and behaviors of users that occur before, during and after use the robots. Combination of superior functionality and usability lead to a good user experiencein using the robots which in the end achieves satisfaction of older persons.

A dichotomic approach to adaptive interaction for socially assistive robots

Socially assistive robotics (SAR) aims at designing robots capable of guaranteeing social interaction to human users in a variety of assistance scenarios that range, e.g., from giving reminders for medications to monitoring of Activity of Daily Living, from giving advices to promote an healthy lifestyle to psychological monitoring. Among possible users, frail older adults deserve a special focus as they present a rich variability in terms of both alternative possible assistive scenarios (e.g., hospital or domestic environments) and caring needs that could change over time according to their health conditions. In this perspective, robot behaviors should be customized according to properly designed user models. One of the long-term research goals for SAR is the realization of robots capable of, on the one hand, personalizing assistance according to different health-related conditions/states of users and, on the other, adapting behaviors according to heterogeneous contexts as well as changing/evolving needs of users. This work proposes a solution based on a user model grounded on the international classification of functioning, disability and health (ICF) and a novel control architecture inspired by the dual-process theory. The proposed approach is general and can be deployed in many different scenarios. In this paper, we focus on a social robot in charge of the synthesis of personalized training sessions for the cognitive stimulation of older adults, customizing the adaptive verbal behavior according to the characteristics of the users and to their dynamic reactions when interacting. Evaluations with a restricted number of users show good usability of the system, a general positive attitude of users and the ability of the system to capture users personality so as to adapt the content accordingly during the verbal interaction.

Acceptance of Remote Assistive Robots with and without Human-in-the-Loop for Healthcare Applications

Assistive social robots aim to facilitate outpatient-care including required safety critical measures. Accepting a robot to perform such measures, e.g., operate in close physical interaction for medical examinations, requires human trust towards the robot. Human-in-the-loop (HIL) applications where the robot is teleoperated by a human expert can help the person to accept even risky tasks performed by a robot. Therefore, the assistive humanoid GARMI was designed to enable HIL applications with varying autonomy. In this study, we use GARMI to understand which tasks in the framework of care may be accepted depending on human socio-demographics and user beliefs as well as the level of robot autonomy. Firstly, we seek to understand the general acceptance of GARMI using the Almere questionnaire. Secondly, we ask adults to rate their willingness to use several functionalities of GARMI. Lastly, we investigate the effect of the introduction method of GARMI on user acceptance. We assemble all relevant factors on acceptance to provide direction in the user-centered design process of assistive robots. The results of 166 participants show that alongside others, trust towards the robot and utilitarian variables such as perceived usefulness are the most influencing factors on the acceptance of GARMI and should be considered for the design of robotic semi-autonomous outpatient-services.

Intelligent Soft Hands and Benchmarking towards General-Purpose Robotic Manipulation

In order to progress the development of intelligent soft hands for general-purpose use in humanoid robots, social assistive robots, adaptive manufacturing, prosthetics and more, we need to rethink our approach to benchmarking. Where previously, hands are compared by their performance in a limited set of tasks, resulting in performance optimisations in the subjective, most common tasks. Instead, we must focus on increasing the hand’s potential at the lowest level, by improving the underlying passive behaviours, in terms of increased behavioural diversity and cheap control.

Extended Interviews with Stroke Patients Over a Long-Term Rehabilitation Using Human–Robot or Human–Computer Interactions

Socially assistive robots (SARs) have been proposed to assist post-stroke patients in performing their exercise during their rehabilitation process, with the trust in the robot identified as an important factor in human–robot interaction. In the current study, we aimed to identify and characterize factors that influence post-stroke patients’ trust in a robot-operated and a computer-operated rehabilitation platform during and after a long-term experience with the platform. We conducted 29 interviews with 16 stroke patients who underwent a long-term rehabilitation process, assisted by either a SAR or a computer interface. The intervention lasted 5–7 weeks per patient, for a total of 229 sessions over 18 months. By using a qualitative research method—extended interviews “in the wild” with stroke patients, over a long-term rehabilitation process—our study reveals users’ perspectives regarding factors affecting trust in the SAR or in the computer interface during their rehabilitation process. The results support the assertion that SARs have an added value in the rehabilitative care of stroke patients; It appears that personal characteristics, such as age and gender, have an effect on the users’ acceptance of a non-human operator as a practice assistant. Our findings support the notion that SARs augment rehabilitative therapies beyond a standard computer; Importantly, patients appreciated different aspects of the non-human operator in the two groups: In the SAR group, users preferred its functional performance over its anthropomorphized social skills; In the Computer group, users highlighted its contribution to the training of their memory skills.

Socially assistive robotics and older family caregivers of young adults with Intellectual and Developmental Disabilities (IDD): A pilot study exploring respite, acceptance, and usefulness.

The need for caregiver respite is well-documented for the care of persons with IDD. Social Assistive Robotics (SAR) offer promise in addressing the need for caregiver respite through 'complementary caregiving' activities that promote engagement and learning opportunities for a care recipient (CR) with IDD. This study explored the acceptability and usefulness of a SAR caregiver respite program responsive to feedback from both young adults with IDD and their older family caregivers (age 55+). Young adults with IDD and caregiver dyads (N = 11) were recruited. A mixed methods research design was deployed in three phases: Phase I with four focus groups to inform the program design; Phase II for program demonstration and evaluation with pre- and post-surveys; and Phase III with post-program interviews for feedback and suggestions. Both young adults with IDD and their caregivers scored favorably the social presence of, social engagement, and satisfaction with robot Pepper. Though there was no significant improvement of caregiving burden/stress as well as well-being of the young adults with IDD based on surveys, results from interviews suggested that the SAR may offer physical/emotional respite to caregivers by providing companionship/friendship as well as promoting independence, safety/monitoring, and interactive engagement with children. SAR has potential in providing respite for older family caregivers. Future studies need a longer program design and larger sample size to develop a promising intervention and test its feasibility and efficacy.

Eliciting a User's Preferences by the Self-Disclosure of Socially Assistive Robots in Local Households of Older Adults to Facilitate Verbal Human-Robot Interaction.

To realize a society in which older adults can live independently in their homes and familiar environments for as long as possible, their lives can be supported by providing appropriate technology. In this case, a new intervention for older people using socially assistive robots (SARs) is proposed; however, previous research has demonstrated that individual differences exist in the use and response to SAR interventions, and it has also been reported that SARs are not used by users in some cases. Therefore, in this study, we developed a self-disclosure function to promote continuous interaction with robots, using a Japanese corpus and self-disclosure items. In this study, we defined the specific requirements and functions of self-disclosure in SARs and developed ten non-arbitrary speech scripts from the field of social psychology using a Japanese corpus and self-disclosure items. To evaluate the effect of self-disclosure in SARs, an SAR was introduced to each household for 20 days, with the consent of seven community-dwelling older adults. Based on the recorded voice interaction data, we analyzed how the number, total time, and quality of verbal interactions changed with the SAR’s self-disclosure. Furthermore, we conducted group interviews with the participants and received positive comments regarding the robot’s self-disclosure. Some participants considered the specific personality of the SAR by accumulating its behavioral characteristics. As a consequence, these results indicate that the robot’s self-disclosure feature is effective in significantly increasing the quantity and quality of verbal interactions with older adults.

Toward Personalized Affect-Aware Socially Assistive Robot Tutors for Long-Term Interventions with Children with Autism

Affect-aware socially assistive robotics (SAR) has shown great potential for augmenting interventions for children with autism spectrum disorders (ASD). However, current SAR cannot yet perceive the unique and diverse set of atypical cognitive-affective behaviors from children with ASD in an automatic and personalized fashion in long-term (multi-session) real-world interactions. To bridge this gap, this work designed and validated personalized models of arousal and valence for children with ASD using a multi-session in-home dataset of SAR interventions. By training machine learning (ML) algorithms with supervised domain adaptation (s-DA), the personalized models were able to tradeoff between the limited individual data and the more abundant less personal data pooled from other study participants. We evaluated the effects of personalization on a long-term multimodal dataset consisting of four children with ASD with a total of 19 sessions, and derived inter-rater reliability (IR) scores for binary arousal (IR = 83%) and valence (IR = 81%) labels between human annotators. Our results show that personalized Gradient Boosted Decision Trees (XGBoost) models with s-DA outperformed two non-personalized individualized and generic model baselines not only on the weighted average of all sessions, but also statistically ( p < .05) across individual sessions. This work paves the way for the development of personalized autonomous SAR systems tailored toward individuals with atypical cognitive-affective and socio-emotional needs.

Socially Assistive Robots as Storytellers that Elicit Empathy

Empathy is the ability to share someone else’s feelings or experiences; it influences how people interact and relate. Socially assistive robots (SAR) are a promising means of conveying and eliciting empathy toward facilitating human-robot interaction. This work examines factors that influence the amount of empathy elicited by a SAR storyteller and users’ perceptions of that robot. We conducted an empirical mixed-design study (N=46) using an autonomous SAR storyteller that told three stories, each with a different human or robot target of empathy. The robot storyteller used the first-person narrative voice (1PNV) with half of the participants and the third-person narrative voice (3PNV) with the other half. We found that the SAR storyteller elicited significantly more empathy when the story target of empathy matched the SAR narrator, i.e., was also a robot. Additionally, the 1PNV robot elicited significantly more empathy and was perceived as more human-like, easy to interact with, and trustworthy than the 3PNV robot. Finally, participants who empathized more with the robot displayed facial expressions consistent with the emotional story content. These insights inform the design of SAR storytellers capable of eliciting empathy toward creating compelling and effective human-robot interactions.

Therapeutic educational robot enhancing social interactions in the management of obesity.

Obesity is a chronic multifactorial pathology determined by many factors, including incorrect eating habits and a low level of physical activity. There is an urgent need to promote a persistent change in lifestyle in obese subjects, but very few individuals maintain long-term results achieved after diet therapies. Therapeutic Education (TE) has taken over an important role as a multidisciplinary intervention aimed at improving lifestyle and at acquiring new skills for the management of the disease. However, only a small portion of patients can maintain participation in such programs and fully benefit from them. Assistive technologies, and in particular assistive social robots, are powerful tools to boost independence and improve participation in educational activities. The aim of the research work described in this article is to evaluate the effect of employing a social robot as a therapeutic educational robot helping the expert therapist in the education activity. This article describes the implementation, deployment, and evaluation of a social educational robot used as a TE assistant. Although we cannot provide statistically significant results due to the limited number of people involved in the experimental protocol, all experimental results show a positive trend, indicating that the robot can enhance the social interactions between the patients and the therapist and among the patients, thus bringing to better overall results of the TE sessions, measured with standard tests for obesity management.