Introducing the Social Robot MARIO to People Living with Dementia in Long Term Residential Care: Reflections

Personalized Cognitive Support via Social Robots

This paper explores the use of personalized cognitive support through social robots to assist the elderly in maintaining cognitive health and emotional well-being. As aging populations grow, the demand for innovative solutions to address issues like loneliness, cognitive decline, and physical limitations increases. The studied social robots utilize machine learning and advanced sensor technology to deliver real-time adaptive interactions, including cognitive exercises, daily task assistance, and emotional support. Through responsive and personalized features, the robot enhances user autonomy and improves quality of life by monitoring physical and emotional states and adapting to the needs of each user. This study also examines the challenges of implementing assistive robots in home and healthcare settings, offering insights into the evolving role of AI-powered social robots in eldercare.

The use of technology by seniors with neurocognitive disorders in long-term care: a scoping review

BACKGROUND

To map the current state of knowledge about the use of technology with seniors with neurocognitive disorders in long-term care to foster interactions, wellness, and stimulation.

METHODS

Cumulative Index to Nursing and Allied Health Literature (CINAHL Plus); MEDLINE; PsycINFO; Embase and Web of Science were searched in eligible literature, with no limit of time, to describe the current use of technology by seniors with neurocognitive disorders in long-term care. All types of literature were considered except for theses, editorial, social media. This scoping review was built around the recommendations of Peters et al. (2020 version). Three researchers collaborated on the selection of articles and independently reviewed the papers, based on the eligibility criteria and review questions.

RESULTS

The search yielded 3,605 studies, of which 39 were included. Most technology type reported was robotics. Included studies reports different positive effects on the use of such technology such as increase of engagement and positive.

CONCLUSION

The study highlights different types and potential benefits of technology for long-term care residents with neurocognitive disorders, emphasizing the crucial need for additional research to refine interventions and their use.

The Role of Coherent Robot Behavior and Embodiment in Emotion Perception and Recognition During Human-Robot Interaction: Experimental Study

BACKGROUND

Social robots are becoming increasingly important as companions in our daily lives. Consequently, humans expect to interact with them using the same mental models applied to human-human interactions, including the use of cospeech gestures. Research efforts have been devoted to understanding users' needs and developing robot's behavioral models that can perceive the user state and properly plan a reaction. Despite the efforts made, some challenges regarding the effect of robot embodiment and behavior in the perception of emotions remain open.

OBJECTIVE

The aim of this study is dual. First, it aims to assess the role of the robot's cospeech gestures and embodiment in the user's perceived emotions in terms of valence (stimulus pleasantness), arousal (intensity of evoked emotion), and dominance (degree of control exerted by the stimulus). Second, it aims to evaluate the robot's accuracy in identifying positive, negative, and neutral emotions displayed by interacting humans using 3 supervised machine learning algorithms: support vector machine, random forest, and K-nearest neighbor.

METHODS

Pepper robot was used to elicit the 3 emotions in humans using a set of 60 images retrieved from a standardized database. In particular, 2 experimental conditions for emotion elicitation were performed with Pepper robot: with a static behavior or with a robot that expresses coherent (COH) cospeech behavior. Furthermore, to evaluate the role of the robot embodiment, the third elicitation was performed by asking the participant to interact with a PC, where a graphical interface showed the same images. Each participant was requested to undergo only 1 of the 3 experimental conditions.

RESULTS

A total of 60 participants were recruited for this study, 20 for each experimental condition for a total of 3600 interactions. The results showed significant differences (P<.05) in valence, arousal, and dominance when stimulated with the Pepper robot behaving COH with respect to the PC condition, thus underlying the importance of the robot's nonverbal communication and embodiment. A higher valence score was obtained for the elicitation of the robot (COH and robot with static behavior) with respect to the PC. For emotion recognition, the K-nearest neighbor classifiers achieved the best accuracy results. In particular, the COH modality achieved the highest level of accuracy (0.97) when compared with the static behavior and PC elicitations (0.88 and 0.94, respectively).

CONCLUSIONS

The results suggest that the use of multimodal communication channels, such as cospeech and visual channels, as in the COH modality, may improve the recognition accuracy of the user's emotional state and can reinforce the perceived emotion. Future studies should investigate the effect of age, culture, and cognitive profile on the emotion perception and recognition going beyond the limitation of this work.

Towards a conceptualisation and critique of everyday life in HRI

This paper focuses on the topic of "everyday life" as it is addressed in Human-Robot Interaction (HRI) research. It starts from the argument that while human daily life with social robots has been increasingly discussed and studied in HRI, the concept of everyday life lacks clarity or systematic analysis, and it plays only a secondary role in supporting the study of the key HRI topics. In order to help conceptualise everyday life as a research theme in HRI in its own right, we provide an overview of the Social Science and Humanities (SSH) perspectives on everyday life and lived experiences, particularly in sociology, and identify the key elements that may serve to further develop and empirically study such a concept in HRI. We propose new angles of analysis that may help better explore unique aspects of human engagement with social robots. We look at the everyday not just as a reality as we know it (i.e., the realm of the "ordinary") but also as the future that we need to envision and strive to materialise (i.e., the transformation that will take place through the "extraordinary" that comes with social robots). Finally, we argue that HRI research would benefit not only from engaging with a systematic conceptualisation but also critique of the contemporary everyday life with social robots. This is how HRI studies could play an important role in challenging the current ways of understanding of what makes different aspects of the human world "natural" and ultimately help bringing a social change towards what we consider a "good life."

A Systematic Literature Review of Decision-Making and Control Systems for Autonomous and Social Robots

In the last years, considerable research has been carried out to develop robots that can improve our quality of life during tedious and challenging tasks. In these contexts, robots operating without human supervision open many possibilities to assist people in their daily activities. When autonomous robots collaborate with humans, social skills are necessary for adequate communication and cooperation. Considering these facts, endowing autonomous and social robots with decision-making and control models is critical for appropriately fulfiling their initial goals. This manuscript presents a systematic review of the evolution of decision-making systems and control architectures for autonomous and social robots in the last three decades. These architectures have been incorporating new methods based on biologically inspired models and Machine Learning to enhance these systems’ possibilities to developed societies. The review explores the most novel advances in each application area, comparing their most essential features. Additionally, we describe the current challenges of software architecture devoted to action selection, an analysis not provided in similar reviews of behavioural models for autonomous and social robots. Finally, we present the future directions that these systems can take in the future.

Older adult perspectives on emotion and stigma in social robots

Introduction

Social robot adoption by older adults and people living with dementia is limited by several barriers, including a lack of emotional alignment with social robots and perceptions of stigma around social robot use. The goal of this work was to address these barriers by engaging end-users in discussions on factors that could affect emotional connection to a social robot and considerations around using a social robot in public.

Methods

We conducted seven 90-min online workshops with older adults with (n = 2) and without dementia (n = 25) and care partners (n = 17). Older adults with and without dementia were in their 50s - 80s, and care partners were in their 30s - 70s. Seven older adults, seven care partners, and one older adult with dementia indicated that they had used a robot before. Online workshops had 4-8 participants each, and began with video demonstrations of pet-like robot MiRo and tabletop robot T-Top, as well as a live demonstration of MiRo. Participants completed the Multi-Dimensional Robot Attitude Scale before the workshops and the Psychosocial Impact of Assistive Devices Scale and two Zoom polls during the workshops. The audio and chat responses from the workshops were transcribed verbatim and content analysis was performed on the transcripts.

Results

Our analysis revealed three broad themes and 10 subthemes. In their discussions on features and applications, participants highlighted preferred forms of communication with a robot and ways in which a robot could support connection between people. For example, robots could improve the quality of communication between care partners and the person for whom they care. While many agreed that a social robot should match their level of emotion and interactivity, participants had different preferences for social robot emotional range and display features. Finally, participants discussed considerations around showing a robot to other people; several participants suggested that a robot could help raise awareness of ageing and dementia while others shared concerns about stigma and attracting negative attention from an audience.

Discussion

Incorporating these findings into the design and implementation of social robots will result in devices that are better-suited to the needs of older adults, people living with dementia, and care partners.

Anthropomorphic Robotic Eyes: Structural Design and Non-Verbal Communication Effectiveness

This paper shows the structure of a mechanical system with 9 DOFs for driving robot eyes, as well as the system's ability to produce facial expressions. It consists of three subsystems which enable the motion of the eyeballs, eyelids, and eyebrows independently to the rest of the face. Due to its structure, the mechanical system of the eyeballs is able to reproduce all of the motions human eyes are capable of, which is an important condition for the realization of binocular function of the artificial robot eyes, as well as stereovision. From a kinematic standpoint, the mechanical systems of the eyeballs, eyelids, and eyebrows are highly capable of generating the movements of the human eye. The structure of a control system is proposed with the goal of realizing the desired motion of the output links of the mechanical systems. The success of the mechanical system is also rated on how well it enables the robot to generate non-verbal emotional content, which is why an experiment was conducted. Due to this, the face of the human-like robot MARKO was used, covered with a face mask to aid in focusing the participants on the eye region. The participants evaluated the efficiency of the robot's non-verbal communication, with certain emotions achieving a high rate of recognition.

The Usability and Impact of a Low-Cost Pet Robot for Older Adults and People With Dementia: Qualitative Content Analysis of User Experiences and Perceptions on Consumer Websites

Background

Worldwide, populations are aging exponentially. Older adults and people with dementia are especially at risk of social isolation and loneliness. Social robots, including robotic pets, have had positive impacts on older adults and people with dementia by providing companionship, improving mood, reducing agitation, and facilitating social interaction. Nevertheless, the issue of affordability can hinder technology access. The Joy for All (JfA) robotic pets have showed promise as examples of low-cost alternatives. However, there has been no research that investigated the usability and impact of such low-cost robotic pets based on perceptions and experiences of its use with older adults and people with dementia.

Objective

The aim of our study was to explore the usability and impact of the JfA robotic cat, as an example of a low-cost robot, based on perceptions and experiences of using the JfA cat for older adults and people with dementia.

Methods

We used a novel methodology of analyzing a large volume of information that was uploaded by reviewers of the JfA cat onto online consumer review sites. Data were collected from 15 consumer websites. This provided a total of 2445 reviews. Next, all reviews were screened. A total of 1327 reviews that contained information about use of the JfA cat for older adults or people with dementia were included for analysis. These were reviews that contained terms relating to “older adults,” “dementia,” and “institutional care” and were published in the English language. Descriptive statistics was used to characterize available demographic information, and textual data were qualitatively analyzed using inductive content analysis.

Results

Most reviews were derived from consumer sites in the United States, and most reviewers were family members of users (ie, older adults and people with dementia). Based on the qualitative content analysis, 5 key themes were generated: prior expectations, perceptions, meaningful activities, impacts, and practicalities. Reviewers had prior expectations of the JfA cat, which included circumstantial reasons that prompted them to purchase this technology. Their perceptions evolved after using the technology, where most reported positive perceptions about their appearance and interactivity. The use of the robot provided opportunities for users to care for it and incorporate it into their routine. Finally, reviewers also shared information about the impacts of device and practicalities related to its use.

Conclusions

This study provides useful knowledge about the usability and impact of a low-cost pet robot, based on experiences and perceptions of its use. These findings can help researchers, robot developers, and clinicians understand the viability of using low-cost robotic pets to benefit older adults and people with dementia. Future research should consider evaluating design preferences for robotic pets, and compare the effects of low-cost robotic pets with other more technologically advanced robotic pets.