Socially Assistive Robots Research Articles

A Framework to Design Engaging Interactions in Socially Assistive Robots to Mitigate Dementia-related Symptoms

People with dementia (PwD) often exhibit behavioral, physiological and social symptoms that affect their relationships and reduce their quality of life. Socially assistive robots (SARs) have proven effective in reducing some of these symptoms. However, the design of SARs for dementia care remains a challenging task. In this paper, we present a human-centered design framework to assist researchers, designers, and roboticist from the conceptualization of engaging prototypes of SARs until the assessment of their efficacy at producing dementia-relevant health outcomes. The framework incorporates several key principles of a Human-Centered Artificial Intelligence (HCAI) approach. It incorporates the needs and perspectives of the different stakeholders into the design and evaluation of the interactions. It fosters accessibility and inclusion thru personalization and encourages human-robot collaboration by facilitating natural and engaging interactions that build trust and rapport. We illustrate the use of the framework with the design of a SAR to support a Cognitive Stimulation Therapy. From this case study we derive a set of design insights for the development of SARs behaviors and interactions for dementia care.

The efficacy of socially assistive robots in improving children’s pain and negative affectivity during needle-based invasive treatment: A systematic review and meta-analysis

BackgroundThe ability of socially assistive robots (SARs) to treat dementia and Alzheimer’s disease has been verified. Currently, to increase the range of their application, there is an increasing amount of interest in using SARs to relieve pain and negative emotions among children in routine medical settings. However, there is little consensus regarding the use of these robots.ObjectiveThis study aimed to evaluate the effect of SARs on pain and negative affectivity among children undergoing invasive needle-based procedures.DesignThis study was a systematic review and meta-analysis of randomized controlled trials that was conducted in accordance with the Cochrane Handbook guidelines.MethodsThe PubMed, CINAHL, Web of Science, Cochrane Library, Embase, CNKI, and WanFang databases were searched from inception to January 2024 to identify relevant randomized controlled trials (RCTs). We used the Cochrane Risk of Bias tool 2.0 (RoB2.0) to assess the risk of bias among the included studies, and we used RevMan 5.4 software to conduct the meta-analysis. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework was used to assess the quality of the evidence.ResultsTen RCTs involving 815 pediatric subjects were selected for this review and reported outcomes related to pain and emotions during IV placement, port needle insertion, flu vaccination, blood sampling, and dental treatment. Children undergoing needle-related procedures with SARs reported less anxiety (SMD= -0.36; 95% CI= -0.64, -0.09) and fewer distressed avoidance behaviors (SMD= -0.67; 95% CI= -1.04, -0.30) than did those receiving typical care. There were nonsignificant differences between these groups in terms of in pain (SMD = -0.02; 95% CI = − 0.81, 0.78) and fear (SMD = 0.38; 95% CI= -0.06, 0.82). The results of exploratory subgroup analyses revealed no statistically significant differences based on the intervention type of robots or anesthetic use.ConclusionsThe use of SARs is a promising intervention method for alleviating anxiety and distress among children undergoing needle-related procedures. However, additional high-quality randomized controlled trials are needed to further validate these conclusions.Trial registrationThe protocol of this study has been registered in the database PROSPERO (registration ID: CRD42023413279).

Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study.

The aging population and the shortage of geriatric care workers are major global concerns. Socially assistive robots (SARs) have the potential to address these issues, but developing SARs for various types of users is still in its infancy. This study aims to examine the characteristics and use patterns of SARs. This study analyzed log data from 64 older adults who used a SAR called Hyodol for 60 days to understand use patterns and their relationship with user characteristics. Data on user interactions, robot-assisted content use, demographics, physical and mental health, and lifestyle were collected. Time series clustering was used to group users based on use patterns, followed by profiling analysis to relate these patterns to user characteristics. Overall, 4 time series clusters were created based on use patterns: helpers, friends, short-term users, and long-term users. Time series and profiling analyses revealed distinct patterns for each group. We found that older adults use SARs differently based on factors beyond demographics and health. This study demonstrates a data-driven approach to understanding user needs, and the findings can help tailor SAR interventions for specific user groups. This study extends our understanding of the factors associated with the long-term use of SARs for geriatric care and makes methodological contributions.

Adapting to My User, Engaging with My Robot: An Adaptive Affective Architecture for a Social Assistive Robot

Affective feedback from social robots is a useful technique for communicating to people whether they are interacting “well” with the robot or not. However, some users, such as people with physical or cognitive difficulties, may not be able to interact in all the desired ways. In these cases, affective feedback from the robot could be excessively negative—an “unhappy” robot, leading to an unrewarding experience for the user. This paper presents a motivation-based architecture for an autonomous multimodal social robot, that incorporates an affective feedback mechanism which generates an affective state by combining the internal needs of the robot and the social interaction quality. The balance between these two factors can dynamically change, allowing the robot to adapt its affective feedback to the user’s interaction style and capabilities. We have implemented this architecture in a simulation and in a MiRo social robot, and report experiments examining the behavior of the system in interactions with different experimental user profiles. The results show that the adaptive mechanism allows the robot to change its affective feedback to give more positive encouragement to users than in non-adaptive cases.

Do we really need this robot? Technology requirements for vestibular rehabilitation: Input from patients and clinicians

BackgroundA main challenge in many types of physical rehabilitation is patient adherence to recommended exercises. Vestibular rehabilitation is the most effective treatment for the symptoms of dizziness, vertigo, imbalance, and nausea caused by vestibular disorders, but adherence levels are particularly low as the rehabilitation program calls for many short exercise sets during the day, which can worsen symptoms and impair balance in the short term. Technological tools have the potential to increase adherence, but to date, there has been no comprehensive analysis, in the context of vestibular rehabilitation, of the specific needs from technology, of its limitations, and of concerns regarding its use. ObjectiveThe aim of the study is to identify the main features required from technology for vestibular rehabilitation, as perceived by patients with vestibular disorders and by vestibular physical therapists, using a socially assistive robot as a test case. We seek here to provide practical information for the development of future vestibular rehabilitation technologies which are based on human-computer interaction (HCI) and human-robot interaction (HRI). MethodsWe conducted a qualitative study with six focus groups (N = 39). Three groups of patients with vestibular disorders (N = 18) and three groups of physical therapists (N = 21) participated in this study. The participants answered structured questions on technologies for vestibular rehabilitation, watched a presentation of two videos of a socially assistive robot (SAR), and completed an online survey. Thematic analysis with a mixed deductive and inductive approach was used to analyze the data. ResultsParticipants preferred phone applications or virtual/augmented reality platforms over an embodied robotic platform. They wanted technology to be adaptive to the different stages of rehabilitation, gamified, easy to use, safe, reliable, portable, and accessible remotely by the therapist. They reported that the technology should provide feedback on the quality and quantity of exercise performance and monitor these factors while considering the tolerability of the ensuing disruptive symptoms. Participants expected that using technology as part of the rehabilitation process would shorten exercise sessions and improve clinical outcomes compared to standard care. SARs for vestibular rehabilitation were perceived as useful mostly for children and patients with chronic vestibular disorders, and their potential use for rehabilitation raised concerns regarding safety, ethics, and technical complexity. ConclusionsAlthough SARs can potentially be used to increase exercise adherence, a phone application appears to be a more suitable medium for this purpose, raising fewer notable concerns from users. We provide a summary of perceived advantages and disadvantages of technology for vestibular rehabilitation, as well as a set of specific requirements from it, which may inform the future development of specific supportive technologies. In addition, the focus group methodology employed demonstrates the importance of participatory design in the development of rehabilitation-supportive technology as participants were able to identify the likely inappropriateness of SARs for the specific case of vestibular rehabilitation.

Attitudes of Special Educators Towards Use of Socially Assistive Robots for Individuals With Autism Spectrum Disorder in Serbia and the United States

Purpose This research explores the initial attitudes of special educators towards socially assistive robots (SAR) and considers how cultural and socioeconomic backgrounds shape these attitudes. Special educators providing services to individuals with autism spectrum disorder (ASD) in the United States and Serbia were surveyed, representing distinct cultural and socioeconomic contexts. Comparing their attitudes offers valuable insights into facilitating SAR adoption for ASD treatment across different cultural landscapes. Additionally, this study conducts a comparative analysis of cultural dimensions in the two countries to contextualize attitudes toward SAR use in ASD treatment. Methods A nonexperimental quantitative approach was employed utilizing a cross-sectional survey design with purposive samples of special educators who provide services to individuals with ASD in the U.S. and Serbia to establish initial attitudes toward SARs. Results The outcomes derived from this investigation reflect the pervasive influence of the cultural contexts. Apprehension has been identified as a significant factor shaping attitudes toward SAR adoption among the Serbian cohort, while a more favorable disposition towards this technology typifies the U.S. participants. The adoption and utilization of SARs, as reported by participants in the U.S., face relatively fewer attitudinal barriers.

Public perception of socially assistive robots for healthcare in the EU: A large-scale survey

This paper presents the results of a large-scale survey (n = 1092) that explored the attitudes and opinions of European Citizens regarding the adoption of socially assistive robots (SARs) for healthcare in the EU. We examined which functions citizens would support and which they consider a threat to trustworthy SARs. We additionally explored the relationships between the perceived vulnerability of the care recipient and acceptance, between attitudes towards robots and gender, age, religious beliefs, and previous experience interacting with SARs, and whether the degree of responsibility taken in performing a role affects acceptance. We also compared attitudes towards robots across European regions. The functions most negatively rated were triage and banning entrance. Privacy raised particular concern. We also found an inverse correlation between the perceived vulnerability of care recipients and acceptance. Additionally, we found a positive relationship between religious beliefs and fear of robots, a positive relationship between previous robot experience and attitudes towards them, and that females have less positive attitudes towards robots than males. Also, the degree of responsibility in a role determined acceptance. Involving citizens in the decisions concerning SARs deployment is important to build a society that people feel is fair in terms of robot coexistence. The results of the survey intend to provide evidence-based support to policies in this area.

Social Assistive Robotics: An Ethical and Political Inquiry Through the Lens of Freedom

The development of social assistive robots for supporting healthcare provision faces a lack of an ethical approach that adequately addresses the normatively relevant challenges regarding its deployment. Current ethical reflection is primarily informed by an individual-centered perspective focused on robots’ implications for their end-users and thereby limited to the dyadic human–robot interaction sphere. Considering that this is tightly correlated to the restricted understanding of core ethical concepts upon which reflection stands, this paper delves into the concept of freedom from a philosophical perspective to unfold its full normative breadth for a critical assessment of technological development. By bringing to the fore the political-structural dimension of freedom and, in turn, elaborating the political dimension of technology, the undertaken philosophical approach discloses freedom as a transversal ethical concept for a normative reflection on technology. Thereby, it broadens the scope of ethical attention beyond the sphere of human–robot interaction and turns attention to the so far overlooked structural dimension of human–robot relations. Drawing on conceptions of freedom as non-domination, among others, the paper approaches social assistive robotics and reexamines the terrain of relevant issues for its development. Since freedom is one major issue upon which current concerns revolve, the undertaken analysis substantially enriches the ongoing ethical discussion on social assistive robotics’ implications for human freedom. In this way, this work contributes to going beyond the current individual-centered ethical perspective by laying conceptual grounds for a comprehensive ethical approach to social assistive robotics’ development.

Exploring the Viability of Socially Assistive Robots for At-Home Cognitive Monitoring: Potential and Limitations

AbstractThe early detection of mild cognitive impairment, a condition of increasing impact in our aging society, is a challenging task with no established answer. One promising solution is the deployment of robotic systems and ambient assisted living technology in the houses of older adults for monitoring and assistance. In this work, we address and discuss a qualitative analysis on the feasibility and acceptability of a socially assistive robot (SAR) deployed in prospective users’ houses to monitor their cognitive capabilities through a set of digitalised neuropsychological tests and spot questions conveniently integrated within the robotic assistant’s daily tasks. We do this by describing an experimental campaign where a robotic system, integrated with a larger framework, was installed in the house of 10 users for a duration of at least 10 weeks, during which their cognitive capabilities were monitored by the robot. Concretely, the robots supervised the users during the completion of the tests and transparently monitored them by asking questions interleaved in their everyday activities. Results show a general acceptance of such technology, being able to carry out the intended tasks without being too invasive, paving the way for an impactful at-home use of SARs.

Toward Ethical Deployment of Social Robots in Education

Purpose: This study explores the role of social robots, also known as socially assistive robots (SARs), in educational settings. It highlights their potential benefits in language learning, STEM education, and personalized learning. The study also aims to identify and address the ethical concerns associated with integrating social robots into education. Method: The paper reviews existing literature on the use of social robots in education and analyzes their potential benefits and ethical issues. The analysis focuses on various educational contexts and the interactions between students and social robots. The review also considers technological advancements and their implications for ethical concerns. Results: Social robots can significantly enhance language learning, STEM education, and personalized learning experiences for students. However, it also identifies several ethical concerns: excessive emotional attachment to robots, privacy issues, potential abuse of robots, bias in the information provided by robots, and accessibility challenges for disadvantaged groups. Conclusion: Addressing the ethical issues related to the use of social robots in education is crucial for maximizing their benefits while ensuring fairness and safety for students. The paper emphasizes the need for collaborative efforts among stakeholders to develop effective and ethical applications of social robots in education, and go forward to both technological advancements and ethical implications.

Designing Socially Assistive Robots Exploring Israeli and German Designers’ Perceptions

Socially assistive robots (SARs) are becoming more prevalent in everyday life, emphasizing the need to make them socially acceptable and aligned with users’ expectations. Robots’ appearance impacts users’ behaviors and attitudes toward them. Therefore, product designers choose visual qualities to give the robot a character and to imply its functionality and personality. In this work, we sought to investigate the effect of cultural differences on Israeli and German designers’ perceptions of SARs’ roles and appearance in four different contexts: a service robot for an assisted living/retirement residence facility, a medical assistant robot for a hospital environment, a COVID-19 officer robot, and a personal assistant robot for domestic use. The key insight is that although Israeli and German designers share similar perceptions of visual qualities for most of the robotics roles, we found differences in the perception of the COVID-19 officer robot’s role and, by that, its most suitable visual design. This work indicates that context and culture play a role in users’ perceptions and expectations; therefore, they should be taken into account when designing new SARs for diverse contexts.

Designing a Socially Assistive Robot to Assist Older Patients with Chronic Obstructive Pulmonary Disease in Managing Indoor Air Quality

Chronic obstructive pulmonary disease (COPD) stems from airflow blockage and lung damage, and indoor air pollution exacerbates COPD, underscoring the necessity for proactive management. Older COPD patients, prone to respiratory and heat-related issues, require crucial assistance, yet their reduced awareness necessitates ongoing education to identify and enhance indoor air quality. To tackle this challenge, we developed a socially assistive robot (SAR) integrating IoT air quality sensors to guide patients in improving indoor air quality (IAQ). This study evaluated IAQ enhancement among older COPD patients using this technology, uncovering a significant reduction in ‘poor air quality alerts’ with a clear linear trend. Although ‘good alerts’ remained consistent, machine learning models predicted improved air quality post-alerts. Consistent alerts serve as a motivating factor for patients to maintain IAQ standards. However, barriers to SAR utilization, such as psychological and operational hurdles, need to be addressed in future research endeavors.

Care Providers’ Perspectives on the Design of Assistive Persuasive Behaviors for Socially Assistive Robots

ObjectivesThe main objectives of this research are (1) to uniquely design assistive behaviors for socially assistive robots using the principles of persuasion from behavioral psychology, and (2) to investigate caregivers’ perspectives and opinions on the use of these behaviors to engage and motivate older adults in cognitive activities. DesignWe developed 10 unique robot persuasive assistive behavior strategies for the social robot Pepper using both verbal and nonverbal communication modes. Robot verbal behaviors were designed using Cialdini's principles of persuasion; nonverbal behaviors included expansive movements of the body. Care providers' perceptions of the quality, strength, and persuasiveness of these robot persuasive behaviors were assessed based on the Perceived Argument Strength Likert scale. Setting and ParticipantsEighteen formal and informal care providers caring for older adults including those living with mild cognitive impairments participated. MethodsAn online survey was designed consisting of short videos of the Pepper robot displaying each behavior. After viewing each video, care providers completed the Perceived Argument Strength Likert scale to evaluate 6 attributes for each behavior. They also provided comments. ResultsResults show robot assistive behaviors using praise with emotion, along with emotion with commitment were the most positively rated by care providers. Qualitative responses indicate robot body language and speech quality were influencing factors in how a person perceives assistance in human-robot interactions. Conclusions and ImplicationsOur findings provide new insights into incorporating persuasive strategies into the design of assistive social robot behaviors with the aim of engaging and motivating older adults in an activity. The majority of care providers rated the robot persuasive behaviors positively. In designing a persuasive socially assistive robot for older adults, it is beneficial to display a combination of persuasive strategies, such as praise and commitment with emotion, to address individual users’ needs and cognitive levels.

How Can Large Language Models Enable Better Socially Assistive Human-Robot Interaction: A Brief Survey

Socially assistive robots (SARs) have shown great success in providing personalized cognitive-affective support for user populations with special needs such as older adults, children with autism spectrum disorder (ASD), and individuals with mental health challenges. The large body of work on SAR demonstrates its potential to provide at-home support that complements clinic-based interventions delivered by mental health professionals, making these interventions more effective and accessible. However, there are still several major technical challenges that hinder SAR-mediated interactions and interventions from reaching human-level social intelligence and efficacy. With the recent advances in large language models (LLMs), there is an increased potential for novel applications within the field of SAR that can significantly expand the current capabilities of SARs. However, incorporating LLMs introduces new risks and ethical concerns that have not yet been encountered, and must be carefully be addressed to safely deploy these more advanced systems. In this work, we aim to conduct a brief survey on the use of LLMs in SAR technologies, and discuss the potentials and risks of applying LLMs to the following three major technical challenges of SAR: 1) natural language dialog; 2) multimodal understanding; 3) LLMs as robot policies.

Can Socially Assistive Robots Be Accepted by Older People Living Alone in the Community?: Empirical Findings from a Social Work Project in China

ABSTRACT A pilot study was undertaken between March 2019 and September 2021, loaning socially assistive robots (SARs) for a 7-day trial to older people living alone in China. Quantitative assessments of participants’ acceptance of technology and loneliness were conducted before and after the intervention, supplemented with qualitative interviews. Unexpectedly, participants’ intention to use SARs decreased significantly, largely due to emotional anxiety. Meanwhile, participants’ level of loneliness remained unchanged. Follow-up interviews revealed anxious emotion, hesitant attitudes, unreal social presence, usability difficulties as contributing factors. The study provides social workers with valuable insights into introducing SARs into community care of older people.

A gamified social robotics platform for intensive therapies in neurorehabilitation

The use of social assistive robots for interactive stimulation has strong potential in neurorehabilitation therapies. It is of particular interest in the case of pediatric patients to promote children’s motivation and adherence, specially when those robots are able of guide gamified activities, as it is the case of NAOTherapist. NAOTherapist is a Social Assistive Robotics (SAR) platform for hands-off rehabilitation based on upper-limb activities, that was originally designed for pediatric patients with Cerebral Palsy (CP) or Obstetric Braxial Plexus Palsy (OBPP). Formerly, it endowed the therapists with tools to perform rehabilitation exercises. This paper proposes the gamification of NAOTherapist in order to incorporate additional characteristics which allow its intensive use in new rehabilitation procedures, such as the Hand-Arm Bimanual Intensive Therapy (HABIT). This intensive therapy setting involves daily activities in several consecutive days, which require a strong engagement of the patients with the therapeutic methods and the acceptation of the NAOTherapist as a rehabilitation system. The gamified system shows very accurate results considering the different aspects defined in the USUS methodology; namely Usability, Social acceptance, User experience and Societal impact.

Robic Socially Assistive Robot Enables Upper Extremity Endurance Training in Spinal Cord Injured Children

Robic's platform emerges as an innovative technological tool demonstrating adequate usability and also a good user experience in an upper limb training program for PedSCI patients. Future developments, incorporating eye-tracking strategies would help determine the engagement with the proposed task

The Town Crier: A Use-Case Design and Implementation for a Socially Assistive Robot in Retirement Homes

The use of new assistive technologies in general, and Socially Assistive Robots (SARs) in particular, is becoming increasingly common for supporting people’s health and well-being. However, it still faces many issues regarding long-term adherence, acceptability and utility. Most of these issues are due to design processes that insufficiently take into account the needs, preferences and values of intended users. Other issues are related to the currently very limited amount of long-term evaluations, performed in real-world settings, for SARs. This study presents the results of two regional projects that consider as a starting hypothesis that the assessment in controlled environments and/or with short exposures may not be enough in the design of an SAR deployed in a retirement home and the necessity of designing for and with users. Thus, the proposed methodology has focused on use-cases definitions that follow a human-centred and participatory design approach. The main goals have been facilitating system acceptance and attachment by involving stakeholders in the robots design and evaluation, overcoming usage barriers and considering user’s needs integration. The implementation of the first use-case deployed and the two-phase pilot test performed in a retirement home are presented. In particular, a detailed description of the interface redesign process based on improving a basic prototype with users’ feedback and recommendations is presented, together with the main results of a formal evaluation that has highlighted the impact of changes and improvements addressed in the first redesign loop of the system.

Personalizing Activity Selection in Assistive Social Robots from Explicit and Implicit User Feedback

AbstractRobots in multi-user environments require adaptation to produce personalized interactions. In these scenarios, the user’s feedback leads the robots to learn from experiences and use this knowledge to generate adapted activities to the user’s preferences. However, preferences are user-specific and may suffer variations, so learning is required to personalize the robot’s actions to each user. Robots can obtain feedback in Human–Robot Interaction by asking users their opinion about the activity (explicit feedback) or estimating it from the interaction (implicit feedback). This paper presents a Reinforcement Learning framework for social robots to personalize activity selection using the preferences and feedback obtained from the users. This paper also studies the role of user feedback in learning, and it asks whether combining explicit and implicit user feedback produces better robot adaptive behavior than considering them separately. We evaluated the system with 24 participants in a long-term experiment where they were divided into three conditions: (i) adapting the activity selection using the explicit feedback that was obtained from asking the user how much they liked the activities; (ii) using the implicit feedback obtained from interaction metrics of each activity generated from the user’s actions; and (iii) combining explicit and implicit feedback. As we hypothesized, the results show that combining both feedback produces better adaptive values when correlating initial and final activity scores, overcoming the use of individual explicit and implicit feedback. We also found that the kind of user feedback does not affect the user’s engagement or the number of activities carried out during the experiment.

System software architecture for advancing human robot interaction by cloud services and multi-robot cooperation

Human-like interactions with robots based on Conversational AI facilitate assistance and teamwork in various contexts. Those interactions are further enhanced by utilizing physical presence and context from the robot's hardware. Robot cooperation is also especially useful, when software or hardware resources have to be shared in a multi-robot system. Therefore, we propose a modular software architecture for multi-robot cooperation that extends the integration of Conversational AI into Socially Assistive Robots, previously suggested by authors. It utilizes a flow-based approach that involves shared repositories and direct or message-driven communication to convey natural language transcriptions among robots in order to support their cooperation. By experiments we evaluated the cooperation between NAOqi based robots and Furhat robot. Our experimental results demonstrate architecture's modularity and adaptability to different cloud services, along with its effectiveness for interactions involving multiple robots.